Invalidity dossier

US 6463413

Speech recognition training for small hardware devices

Current assignee: Panasonic Holdings Corp

Added 9/25/2026, 1:23:54 AM

At a glanceNo PTAB challenges1 lawsuit on fileSoftware Technology & Computing Systems (T)

Active provider: DeepSeek · deepseek-v4-flash

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Patent summary

Title, assignee, inventors, filing/issue dates, abstract, and a plain-language overview of the claims.

✓ Generated

I'll search for authoritative records on this specific patent.

Let me check the litigation history and any 2026 appellate activity specifically for this patent.

USPTO / CAFC search results for US 6,463,413

I searched for this exact patent number (no similar-number substitution). Findings below are grounded in the Google Patents full-text record (fetched 2026-09-25), the EPO/PIS family record, and the USPTO‑derived mirrors, plus targeted docket searches. Where I could not confirm something authoritatively, I say so explicitly.

Bibliographic data (high confidence — from the patent record itself)

Field Value
Patent number US 6,463,413 B1 (not "6463413" formatted elsewhere)
Title Speech recognition training for small hardware devices
Application number US 09/295,276
Filing date 1999-04-20
Priority date 1999-04-20
Issue/grant date 2002-10-08
Inventors Ted H. Applebaum; Jean-Claude Junqua (recorded as "APPLEBAUM, TED" and "JUNQUA, JEAN-CLAUDE" in the 1999 assignment)
Original assignee Matsushita Electric Industrial Co., Ltd.
Current assignee(s) per Google Patents Panasonic Holdings Corp; Intertrust Technologies Corp
Assignment chain Matsushita Electric Industrial → Panasonic Intellectual Property Corporation of America (2014-05-27) → Intertrust Technologies Corporation (2016-06-27); security interest to Origin Future Energy Pty Ltd (2020-03-18), released 2023-02-14
Legal status Expired – Lifetime; anticipated expiration 2019-04-20
Classifications G10L 15/00, 15/28, 15/30, 15/06, 15/08, 15/18, 15/183, 15/187, 15/22, G10L 2015/0638
Family EP 1047046 B1 and DE 60003971 T2 ("Distributed architecture for training a speech recognition system"), filed 2000-03-22 claiming the same 1999-04-20 priority

Abstract (verbatim)

"A distributed speech processing system for constructing speech recognition reference models that are to be used by a speech recognizer in a small hardware device, such as a personal digital assistant or cellular telephone. The speech processing system includes a speech recognizer residing on a first computing device and a speech model server residing on a second computing device. The speech recognizer receives speech training data and processes it into an intermediate representation of the speech training data. The intermediate representation is then communicated to the speech model server. The speech model server generates a speech reference model by using the intermediate representation of the speech training data and then communicates the speech reference model back to the first computing device for storage in a lexicon associated with the speech recognizer."

Plain-language overview of the independent claims

There are four independent claims: 1, 11, 22, and 32 (everything else is dependent). All four express the same underlying idea in different statutory forms.

Claim 1 — System claim (generic two-device architecture).
Covers a speech-processing system with two cooperating parts: (a) a speech recognizer on a "first computing device" that takes in speech training data, converts it to an intermediate representation, and sends that representation over a network to a second device; (b) a speech model server on the second computing device that receives the intermediate representation, builds a speech reference model from it, and sends the model back; and (c) a lexicon on the first device that stores the returned model. The core insight: the small device does the cheap part (feature extraction) and the remote server does the expensive part (model building).

Claim 11 — Distributed system claim, PDA-specific.
Same distributed architecture, but the "first computing device" is a personal digital assistant and the input means captures speech training data at the PDA. The server is on a second computing device connected to the PDA via a network; the returned reference model is stored in a lexicon on the PDA. (Dependent claims 12–13 add a stylus/display-pad/handwriting-recognition front end, with the alphanumeric text segmented into a symbol sequence serving as the intermediate representation.)

Claim 22 — Distributed system claim, cellular-handset-specific.
Same architecture again, but the first device is a cellular telephone handset. Input means captures speech training data at the handset; the handset's recognizer sends the intermediate representation over a network to the model server, which returns a reference model stored in a handset-resident lexicon. (Dependent claim 23 specifies a keypad capturing alphanumeric data instead of audio.)

Claim 32 — Method claim.
The method counterpart: (1) collect speech training data at a first computing device; (2) process it on that device into an intermediate representation; (3) communicate the intermediate representation over a network to a second computing device; (4) create a speech reference model from the intermediate representation at the second device; and (5) communicate the reference model back to the first device for use in the speech recognition system.

Notable dependent-claim subject matter (for context)

  • Text path: alphanumeric text as training data, with the intermediate representation being a sequence of symbols (claims 2, 13, 23).
  • Audio path: audio captured and digitized into a vector of parameters indicative of short-term spectral shape (claims 3, 4, 17, 27); the vector may be PCM, μ-law PCM, filter bank energies, line spectral frequencies, or cepstral coefficients (claims 5, 18, 28).
  • Server-side resources: a database of speaker-independent models that can be looked up first (claims 6, 14, 24); a phoneticizer producing multiple phonetic transcriptions plus a model trainer (claims 7, 15, 25); an HMM phone-model database used to decode the parameter vectors into a phonetic transcription (claims 8, 19, 29).
  • Multi-repetition enrollment: at least two training repetitions producing a sequence of parameter vectors, with server-side alignment, then mean/variance computation to build the model (claims 9–10, 20–21, 30–31).

Litigation / CAFC 2026 findings — with an important caveat

  • No Federal Circuit 2026 docket involving US 6,463,413 was found. Searches of CAFC 2026 materials (scheduled-case lists, Federal Circuit updates, certiorari filings) returned no appeal, IPR appeal, or other Federal Circuit proceeding naming this patent. I cannot affirmatively prove a negative, but I found no evidence of any 2026 appellate activity.
  • A caveat on the Delaware litigation pointer. The Google Patents page carries a generic litigation link to Delaware District Court case 1:17-cv-01484. When I searched that case number, it resolved to Nuance Communications, Inc. v. MModal LLC (D. Del., filed 2017-10-23, Judge Maryellen Noreika; patents at issue included U.S. 7,379,946, 6,766,295, and others belonging to Nuance). I found no authoritative indication that US 6,463,413 was an asserted patent in that case. The 1:17-cv-01484 docket entry on Google Patents should therefore not be treated as reliable evidence that this patent was litigated. Treat the Delaware litigation linkage as unverified.
  • No IPR/PGR identified. I found no post-grant proceeding (IPR, PGR, CBM) specific to this patent in the search results.

Bottom line

US 6,463,413 is a 1999-priority Matsushita (later Panasonic → Intertrust) patent claiming the distributed client-server split for speech-reference-model training: the small device extracts an intermediate representation and ships it to a server, which builds the model and sends it back to the device's lexicon. It issued 2002-10-08 and expired 2019-04-20, so it is no longer in force. I found no 2026 CAFC activity, and the one litigation pointer on the Google Patents page (D. Del. 1:17-cv-01484) appears to relate to a different patent owner's case.

Generated 9/25/2026, 4:48:03 AM

Cases on file (1)

Group view →

Specific litigation cases in our database that name US patent 6463413. The free-form analysis below may also discuss cases beyond this list.

Litigation summary

Past and pending lawsuits — plaintiffs, defendants, jurisdictions, outcomes, and notable rulings.

✓ Generated

I'll research litigation involving US patent 6463413. Let me search multiple sources.

Let me search more targeted sources for this specific patent.

The patent record shows a Delaware case. Let me dig into that specific case and related Intertrust assertions.

Litigation Involving U.S. Patent No. 6,463,413 ("Speech recognition training for small hardware devices")

Bottom line / confidence caveat: My searches did find exactly one litigation record tied to this patent number, but the record is thin and I was unable to independently open and verify the underlying docket page within the available search steps. I am reporting what is verifiable and flagging clearly what is not. Per your instruction, I did not substitute similar numbers.


1. Confirmed record (from the patent's own litigation metadata)

The Google Patents record for US6463413B1 (fetched 2026-09-25, https://patents.google.com/patent/[US6463413](/patent/US6463413)/en) contains a litigation entry:

Field Value
Plaintiff(s) Not stated in the record provided
Defendant(s) Not stated in the record provided
Jurisdiction Delaware District Court (D. Del.)
Case number 1:17-cv-01484
Filing date Not stated in the record (case number format implies a 2017 filing)
Outcome/status Not stated; the entry is labeled only "litigation / Critical"
Source cited by the record Unified Patents Litigation Data — https://portal.unifiedpatents.com/litigation/Delaware%20District%20Court/case/1%3A17-cv-01484

This is the only litigation reference for patent 6,463,413 that appeared in the source materials. The parties, outcome, and status are not supplied by that record.

2. Important ownership context (relevant to any assertion)

The public assignment history on the same page shows the patent moving from Matsushita Electric Industrial Co., Ltd. (original assignee, filed 1999-04-20) → Panasonic Intellectual Property Corporation of America (2014-05-27) → Intertrust Technologies Corporation (2016-06-27). That places the 2017 Delaware case after Intertrust acquired the patent, which is consistent with Intertrust's known patent-assertion activity in that period. I could not, however, confirm from the available results that '413 was asserted in any of Intertrust's well-documented campaigns (e.g., Intertrust v. Microsoft, Intertrust v. Apple (N.D. Cal., No. C13-1235), Intertrust v. Cinemark (E.D. Tex., 2:19-cv-00266), or Dolby Labs. v. Intertrust (N.D. Cal., 3:19-cv-03371)) — those suits involved different Intertrust/Panasonic patents, not 6,463,413.

3. What I could NOT confirm (be cautious here)

  • When I searched the literal case number 1:17-cv-01484 (D. Del.), the result returned was Nuance Communications, Inc. v. MModal LLC (D. Del.) on CourtListener. I was not able to verify that U.S. Patent 6,463,413 was actually asserted in that case, and Nuance is not a recorded owner of the '413 patent. I therefore cannot state as fact that Nuance v. MModal is the case referenced by the Unified Patents litigation link. Treat any identification of the parties as unverified.
  • I could not retrieve the Unified Patents case page itself, so the plaintiff/defendant/outcome fields for the Delaware matter remain blank.

4. Preliminary assessment

  • One litigation record exists for U.S. 6,463,413: a Delaware District Court case, No. 1:17-cv-01484, sourced from Unified Patents. This is a real, patent-specific citation, not a similar-number match.
  • No outcome is known; the patent itself is marked "Expired – Lifetime" (anticipated expiration 2019-04-20 per the record), so any 2017 case would have been prosecuted against a patent nearing or past expiration.
  • No other litigation naming this patent appeared in my results.

5. Recommended next steps to firm this up (I did not have remaining search steps to run these)

  1. Open the Unified Patents litigation page directly: https://portal.unifiedpatents.com/litigation/Delaware%20District%20Court/case/1%3A17-cv-01484 (this should name the parties).
  2. Pull the PACER docket for D. Del. 1:17-cv-01484 and check the complaint's asserted patent numbers.
  3. Cross-check CourtListener/RECAP and RPX Insight for the '413 patent to confirm whether it was among the asserted patents and to capture the final disposition (settlement, dismissal, judgment).

If you'd like, I can run those targeted lookups (Unified Patents case page, PACER/RECAP docket, RPX) to fill in plaintiff, defendant, filing date, and outcome.


Note on method: I searched for the exact string "6463413" and the Delaware case number, and disregarded results concerning other patents (e.g., the '646 patents in SCA v. First Quality and HQ Specialty Pharma v. Fresenius, which are unrelated to 6,463,413).

Generated 9/25/2026, 4:48:18 AM

Proceedings on file (0)

All PTAB activity →

AIA trial proceedings (IPR / PGR / CBM) filed at the USPTO Patent Trial and Appeal Board against this patent. Sourced from the USPTO Open Data Portal and refreshed every six hours; each proceeding number deep-links to the PTAB E2E docket.

No PTAB proceedings on file. This patent has not been challenged via IPR, PGR, or CBM. The absence is itself a signal — well-asserted patents eventually attract IPRs. The LLM analysis below may surface filings the ODP feed hasn’t indexed yet.

PTAB challenges

AIA trial proceedings at the USPTO Patent Trial and Appeal Board — IPR, PGR, and CBM. Petitioners, judge panels, claim-level invalidation outcomes from Final Written Decisions, and Federal Circuit appeals. The single most important defensive datapoint after litigation history.

✓ Generated

I'll verify the canonical "no proceedings on file" result against live sources before drafting.

Let me run a couple more targeted checks before concluding.

Proceedings overview

Zero AIA trial proceedings are on file for US 6,463,413. The USPTO Open Data Portal returns no IPR, PGR, or CBM for this patent, and independent web searches (Patent Trial and Appeal Board, PTAB E2E/public petition repositories, Docket Alarm mirrors, Unified Patents' portal page for US-6463413-B1, CourtListener/Federal Circuit materials) surfaced no petition, institution decision, final written decision, or appeal naming this patent. The breakdown is therefore: 0 active / 0 claims invalidated / 0 claims sustained / 0 settled / 0 institution denied.

The bottom-line defensive posture is unusual and, for a defendant, favorable — but for a reason that has nothing to do with PTAB hardening: the patent has never been tested at the Board, and it cannot be meaningfully tested now because it expired on 2019-04-20. There is no "hardened" surviving claim set to fight; there is an untested-but-dead patent. That is a very different defensive story from "the patent has survived two IPRs," and it should be pleaded and papered accordingly.


No proceedings to enumerate — what the empty record actually means

Because the structured PTAB block is canonical and returns zero, and my web checks found nothing the ODP had missed, I am not listing proceeding entries. Inventing case numbers is off the table. Instead, here is the interrogation of the empty set, structured the way you would want a defensive posture memo.

(a) The record I checked

Source type Result for US 6,463,413
USPTO ODP structured "PTAB proceedings on file" block No AIA trial proceedings (as of most recent ingest)
PTAB web/petition repositories (ptacts.uspto.gov, docket mirrors) No petition found naming this patent
Unified Patents portal (portal.unifiedpatents.com/patents/patent/US-6463413-B1) Patent page exists, but it is a bibliographic/prior-art page only — no IPR or administrative challenge attributed to Unified
Federal Circuit / CAFC 2026 dockets No appeal (consistent with the prior section's finding)
Ex parte reexamination No reexamination found; I cannot prove a negative here, and reexam records are not in the ODP AIA-trial field, so treat "no reexam" as unverified rather than established

(b) Why the absence is credibly explained (and why that matters to you)

Three structural reasons explain why this patent never attracted an IPR, and each has a tactical read for a defendant being asserted against today:

  1. Timing within the AIA window. IPR/PGR/CBM became available on 2012-09-16. This patent issued on 2002-10-08 and expired on 2019-04-20 — a usable IPR window of roughly 6.6 years, and one in which the patent was apparently never being asserted in a way that justified a $500K+ petition.
  2. No visible assertion campaign against deep-pocketed targets. The related Google Patents litigation pointer (D. Del. 1:17-cv-01484) was already flagged as unreliable and appears to belong to a different patent owner's case (Nuance v. MModal). No Intertrust or Panasonic assertion of this patent was surfaced in searches — contrast the Intertrust DRM patents that did draw IPRs (e.g., IPR2020-01123 on U.S. 6,157,721, arising from the Dolby/Intertrust dispute). Speech-recognition training architecture was not Intertrust's assertion theme; digital-cinema DRM was.
  3. Expiration mooted the value of a challenge. By the time Intertrust acquired the patent (assignment recorded 2016-06-27), only ~2.8 years of term remained, and the patent expired 2019-04-20. A petitioner weighing an IPR against a nearly-expired patent rarely files.

(c) Estoppel landscape — wide open, but for an unsatisfying reason

  • No § 315(e)(2) estoppel exists against anyone. Because no FWD ever issued, no petitioner, real party in interest, or privy is barred from raising any § 102/§ 103 ground. There is no estoppel to route around.
  • No § 315(b) one-year bar, no § 315(a)(1) civil-action bar, no § 325(a) bar is implicated by any prior PTAB filing, because there was none.
  • The practical bar is temporal, not estoppel-based. IPR of an expired patent is not categorically prohibited where past damages remain live (the Board has instituted on expired patents under the theory that a § 315 controversy persists), but the relief is worthless: a "canceled" claim of an expired patent produces no prospective freedom-to-operate benefit. Combined with the current Director's "settled expectations" discretionary-denial practice — which expressly weighs how long a patent has been in force, and which has driven institution rates down to roughly 30–40% as of July 2026 — an IPR petition here would face near-certain discretionary denial. See https://natlawreview.com/article/changes-ptab-and-takeaways-life-sciences-stakeholders and https://www.mintz.com/insights-center/viewpoints/2231/2025-08-28-ptab-pendulum-swings-how-ipr-denials-are-reshaping.

(d) Pattern signals

  • No serial-petitioner pattern: no petitioner has ever filed on this patent, so there is no "repeat challenger" or IPR-troll dynamic to exploit.
  • No aggressive PTAB-appeal posture by the patent owner: Intertrust's appellate energy went to its DRM portfolio, not here.
  • No defensive aggregator in the chain: Unified Patents maintains a page for the patent but did not file. Do not read the portal listing as prior art curation or as a prior validity challenge — it is not.
  • One real prior-art signal that is worth mining, and it is in the family file: the EPO search report for the family member EP 1 047 046 (A3 published 2002-05-22) lists exactly three references — US 5,054,082 (Motorola, 1991), US 5,212,730 (Texas Instruments, 1993 — "Voice recognition of proper names using text-derived recognition models"), and US 5,732,187 (Texas Instruments, 1998 — "Speaker-dependent speech recognition using speaker independent models"). These same three appear in the "Family Cites Families" set on the Google Patents record. The German translation of the granted EP claims (DE 600 03 971 T2, published 2004-05-27) goes further and expressly acknowledges US-A-5054082 as known art disclosing downloading pre-existing speech models from a remote server. See https://patentimages.storage.googleapis.com/14/3b/94/1f35d2ed95a7ac/EP1047046A3.pdf and https://patentimages.storage.googleapis.com/bc/8d/d2/bc579df5c89ea5/DE60003971T2.pdf. That is an admission in the patent family's own file that the remote-server-download concept predates it — the most useful invalidity lead available on this patent, and one the patentee itself put in the record.

Strategic summary

Claim status. All 32 claims of US 6,463,413 — the four independent claims 1, 11, 22, 32 and the 28 dependents — are UNTESTED. None is CANCELED; none is SUSTAINED. There is no FWD, no certificate of cancellation, and no reexamination certificate narrowing any claim. Verified against the full claim set at https://patents.google.com/patent/[US6463413B1](/patent/US6463413B1)/en. The only claim-level change of record is the procedural posture: the patent expired on 2019-04-20 (legal status "Expired – Lifetime"; anticipated expiration 2019-04-20), so no claim can be infringed by conduct occurring on or after that date, and damages are limited to the pre-expiration window with the six-year look-back of 35 U.S.C. § 286.

Estoppel landscape. There is no PTAB estoppel at all — no § 315(e)(2) bar binds any party, because no IPR/PGR/CBM ever reached a FWD. A defendant today is free to run any § 101/§ 102/§ 103/§ 112 theory in district court or at the Board, subject only to ordinary IPR § 315(b) timing and the Director's discretionary-denial practice. In practical terms, your prior-art runway is the entire field, with the family-file references above (US 5,054,082, US 5,212,730, US 5,732,187) as the first place to start.

Pattern signals. No serial petitioner; no patent-owner appellate aggression on this patent; no defensive aggregator actually filing. The absence of any IPR over the ~20 years this patent was enforceable and ~6.6 years IPR was available is itself informative: well-asserted patents eventually attract IPRs, and this one was never asserted hard enough to warrant one. The corollary is that if you are now receiving a demand letter on US 6,463,413, the assertion is likely coming from a party that acquired a long-expired, never-tested asset late in its life (Intertrust took assignment in 2016; Panasonic IP Corp of America in 2014) — a profile consistent with portfolio-monetization demand letters rather than an operating-company campaign.


Recommended next steps

1. Lead with expiration, not invalidity. The highest-value, lowest-cost defense is temporal. The patent expired 2019-04-20; its "Expired – Lifetime" status is recorded at https://patents.google.com/patent/US6463413B1/en. Demanding royalties on post-2019-04-20 activity — which is most of the relevant market today — is not viable. Build your chronology first: the accused product's first sale date, the last sale before expiration, and the § 286 six-year damages floor relative to a complaint presumably filed in 2025–2026 (i.e., the recoverable period may be short or entirely gone).

2. Do not file an IPR — and say so in your litigation budget. With no live claims to cancel, institution rates at ~30–40% and the Director's "settled expectations" factor weighing against a patent in force since 2002, an IPR here is negative-expected-value. This is the rare case where the correct PTAB advice is: no PTAB. Note this explicitly — "the absence of PTAB activity is not an opportunity, it's a signal that the remedy is moot."

3. Mine the family file for invalidity, don't invent it. Pull and chart:

  • US 5,054,082 (Motorola) — cited in the EP search report and expressly acknowledged in the EP family as teaching remote-server model downloading.
  • US 5,212,730 (TI) — "Voice recognition of proper names using text-derived recognition models," directly on the text-to-model (phoneticizer) path of claims 2, 13, 23.
  • US 5,732,187 (TI) — "Speaker-dependent speech recognition using speaker independent models," directly on the speaker-independent-lookup path of claims 6, 14, 24.
  • The § 102(b) printed publication, Morin & Applebaum, "Word Hypothesizer Based on Reliably Detected Phoneme Similarity Regions," 1995, pp. 897–900 — authored by the named inventor and cited on the face of the patent as non-patent literature, i.e., the patentee's own pre-1999 publication.
    Links: https://patentimages.storage.googleapis.com/14/3b/94/1f35d2ed95a7ac/EP1047046A3.pdf (EP search report annex); https://patentimages.storage.googleapis.com/bc/8d/d2/bc579df5c89ea5/DE60003971T2.pdf (granted-claim German translation with the US 5,054,082 acknowledgement).

4. If a district-court case is already filed, consider a targeted § 101 / § 112 posture instead of § 103. With no PTAB record to borrow from, your validity attack will be litigated from scratch. The claims recite a two-device functional split with "input means" language in claims 11–31 (a § 112(f) minefield) and near-identical independent claims 1/11/22/32 differing only in the nominated device (generic / PDA / cellular handset) — a written-description/enablement and double-patenting angle that costs far less to develop than a full prior-art campaign.

5. Flag the litigation-link error defensively. The Google Patents page carries a Delaware litigation pointer (1:17-cv-01484) that — per the prior section — resolves to Nuance Communications, Inc. v. MModal LLC and does not appear to involve this patent. If opposing counsel cites the Google Patents "litigation" field as evidence of a well-tested, heavily-asserted patent, that is factually wrong and should be corrected on the record.

Verification note on scope. Everything above is stated at the confidence the sources support. The affirmative finding — zero AIA trial proceedings — rests on the canonical ODP structured field plus independent web corroboration. The negative findings about ex parte reexamination and about any EPO opposition to the family member EP 1 047 046 B1 (granted 2003-07-23; DE translation published 2004-05-27) are not confirmed and should be verified directly in USPTO PatentCenter / EPO Register before being relied on in a filing.

Generated 9/25/2026, 4:48:35 AM

Ownership chain (6)

Asserters network →

Structured records extracted from the assignment-history narrative below. Each entity links to its full ownership-network profile.

  1. 1999-04-20 · Assignment

    Ted H. Applebaum; Jean-Claude JunquaMATSUSHITA ELECTRIC INDUSTRIAL CO., LTD.

  2. 2008-10-01 · Change of Name

    MATSUSHITA ELECTRIC INDUSTRIAL CO., LTD.PANASONIC CORPORATION

    change of name only

  3. ? · recorded 2014-05-27 · Assignment

    PANASONIC CORPORATIONPANASONIC INTELLECTUAL PROPERTY CORPORATION OF AMERICA

    internal reorg

  4. ? · recorded 2016-06-27 · Assignment

    PANASONIC INTELLECTUAL PROPERTY CORPORATION OF AMERICAIntertrust Technologies Corporation

    transfer-to-asserter

  5. ? · recorded 2020-03-18 · Security Agreement

    Intertrust Technologies CorporationOrigin Future Energy Pty Ltd

    securitization

  6. ? · recorded 2023-02-14 · Release

    Origin Future Energy Pty LtdIntertrust Technologies Corporation

    securitization

Assignment history

Inventors, original assignee, and the chain of ownership recorded with the USPTO — including the correspondent attorney who recorded each assignment, since shell-LLC chains often share one repeat-player attorney even when the entity names look unrelated. Surfaces NPE / patent-troll patterns: shell-entity transfers, known asserters in the chain, repeat correspondent fingerprints, pre-litigation assignments, and bankruptcy fire-sales.

✓ Generated

I'll research the assignment record for US 6,463,413 across USPTO assignment records and related sources.

Let me dig into the specific USPTO assignment records and the Intertrust/Panasonic transactions.

Let me try to locate the specific reel/frame records via the USPTO assignment API and related mirrors.

Important data limitation (read first)

I was not able to retrieve reel/frame numbers or correspondent-of-record data for US 6,463,413. The USPTO Assignment Center (assignmentcenter.uspto.gov) and the legacy assignment.uspto.gov Patent Assignment Search are JavaScript/API-driven and were not reachable or indexable through the search tools available to me on this pass; no third-party mirror (uspto.report, Unified Patents, FreePatentsOnline) surfaced a reel/frame for this patent either.

What I can ground is the legal-events assignment record carried on the Google Patents page (which is derived from the USPTO assignment database) plus the family/owner data. Those events give me dates, conveyance types, assignors and assignees — but not reel/frame or correspondent. I have not invented reel/frame numbers to fill the gap. Every reel/frame field below is marked [not retrieved] rather than guessed. This is itself a material limitation on the "repeat correspondent" signal (see §NPE signals 3).

Sources used: Google Patents legal events for US 6,463,413 (fetched 2026-09-25); Unified Patents patent portal entry US-6463413-B1 (lists current assignee Intertrust Technologies Corp); EPO/PIS family record.


Inventors

Inventor Employer at filing (as determinable)
Ted H. Applebaum Matsushita Electric Industrial Co., Ltd. — U.S. speech R&D operation (Panasonic Speech Technology Laboratory, Santa Barbara, CA)
Jean-Claude Junqua Matsushita Electric Industrial Co., Ltd. — same U.S. speech R&D operation

Both inventors are recorded as assignors on the 1999 assignment to MATSUSHITA ELECTRIC INDUSTRIAL CO., LTD. (Google Patents legal events; recorded as "APPLEBAUM, TED" and "JUNQUA, JEAN-CLAUDE"). Junqua is a prolific, long-tenured Panasonic speech researcher and his name recurs across the same lab's patent output (the patent itself cites the lab's own Morin/Applebaum work, U.S. 5,684,925 / 5,822,728 / 5,825,977, and the examiner-cited non-patent literature is Applebaum/Morin/Junqua lab output).

Unusual patterns — assessment: None found on the face of the record. Both inventors assigned to the parent at filing, which is the normal pattern for a corporate R&D lab. There is no evidence in the assignment record that either inventor departed within 12 months of filing, and I could not confirm departure dates from any authoritative source — flagged unclear, not "no." (Junqua's later patent output suggests he remained with Panasonic well past 2000, but I could not verify that for this pass and am not treating it as established.) One mildly notable feature: U.S.-resident inventors assigning directly to the Japanese parent rather than to a U.S. subsidiary — common for Matsushita/Panasonic and not, by itself, a fire-sale tell.


Original assignee

Matsushita Electric Industrial Co., Ltd. (Osaka, Japan) — the entity named on the issued patent (front page: "Matsushita Electrical Industrial Co., Ltd.").

  • Line of business: Diversified consumer electronics — the era's Panasonic-brand TVs, audio, and, directly relevant here, PDAs and cellular handsets, the two device classes the specification describes (FIGS. 1 and 2: PDA voice-dial address book; cellular handset voice dialing).
  • Did they ship a product embodying the claims? Plausible but unconfirmed. Panasonic sold both PDAs and cellular handsets in this window, and the specification is written as a product-embodiment disclosure. I found no evidence that a shipped Panasonic product implemented the specific client/server training split claimed. Mark unclear.
  • Current status (as the original assignee): No longer the owner. Matsushita Electric Industrial Co., Ltd. changed its name to Panasonic Corporation on 2008-10-01 (well-established corporate fact) and has since restructured into Panasonic Holdings Corp. It never went bankrupt — it sold/divested the asset. The Google Patents "current assignee" field lists Panasonic Holdings Corp and Intertrust Technologies Corp; only Intertrust holds the operative title per the assignment chain below.

Assignment timeline

Chronological, from the Google Patents legal-events record for US 6,463,413. Reel/frame and correspondent are [not retrieved] for every entry (see limitation note). Dates shown are the dates carried in the record (recordation dates for the post-issuance events).

  1. 1999-04-20 (executed on/near filing) / recorded 1999-04-20 — Reel [not retrieved]/[not retrieved]

    • Conveyance: Assignment of assignors' interest (inventor → company)
    • Assignor: Ted H. Applebaum; Jean-Claude Junqua
    • Assignee: Matsushita Electric Industrial Co., Ltd.
    • Correspondent: [not retrieved]
    • Context: Original employment/invention assignment at filing — normal corporate capture, not a transfer.
  2. 2008-10-01 (name change) — no separate asset transfer

    • Conveyance: Change of name only (Matsushita Electric Industrial Co., Ltd. → Panasonic Corporation)
    • Assignor / Assignee: Same legal entity
    • Correspondent: [not retrieved]
    • Context: Corporate rename. For this patent the later record lists "PANASONIC CORPORATION" as assignor, consistent with the name having been captured; I could not confirm whether a §3.21 name-change recordation exists for this patent specifically — unverified.
  3. 2014-05-27 (date as carried) — Reel [not retrieved]/[not retrieved]

    • Conveyance: "Assignment of assignor's interest"
    • Assignor: Panasonic Corporation
    • Assignee: Panasonic Intellectual Property Corporation of America (Panasonic's U.S. IP-holding subsidiary, Torrance, CA)
    • Correspondent: [not retrieved]
    • Context: Internal corporate reorganization — parent-to-IP-holding-subsidiary consolidation, not an arm's-length sale.
  4. 2016-06-27 (date as carried) — Reel [not retrieved]/[not retrieved]

    • Conveyance: "Assignment of assignors' interest"
    • Assignor: Panasonic Intellectual Property Corporation of America
    • Assignee: Intertrust Technologies Corporation
    • Correspondent: [not retrieved]
    • Context: Transfer out of the Panasonic group to a third-party licensing entity. Because the assignor is the bulk U.S. IP-holding subsidiary and the assignee is a portfolio-scale licensor, this reads as a portfolio-level disposition, not a patent-specific sale — but I could not confirm the transaction document or its scope in this pass. Treat "portfolio-level" as inference.
  5. 2020-03-18 (date as carried) — Reel [not retrieved]/[not retrieved]

    • Conveyance: Security interest (not a title transfer)
    • Assignor (debtor): Intertrust Technologies Corporation
    • Assignee (secured party): Origin Future Energy Pty Ltd
    • Correspondent: [not retrieved]
    • Context: Securitization / secured financing — this patent pledged as collateral. Title stayed with Intertrust.
  6. 2023-02-14 (date as carried) — Reel [not retrieved]/[not retrieved]

    • Conveyance: Release by secured party
    • Assignor: Origin Future Energy Pty Ltd
    • Assignee: Intertrust Technologies Corporation
    • Correspondent: [not retrieved]
    • Context: Lien release — collateral freed; consistent with debt repayment/refinancing, not an asset movement.

Net effect: title runs Matsushita → (rename) Panasonic → Panasonic IP Corp of America → Intertrust Technologies Corporation, with a 2020–2023 security-interest pledge-and-release layered on top. Intertrust is the last recorded assignee; the patent itself expired 2019-04-20.


Timeline diagram

timeline
    title Ownership of US 6463413
    1999 : Inventors assign to Matsushita Electric
    2008 : Matsushita renamed Panasonic Corporation
    2014 : Transferred to Panasonic IP Corp of America
    2016 : Transferred to Intertrust Technologies
    2019 : Patent expires
    2020 : Security interest to Origin Future Energy
    2023 : Lien released by secured party

NPE / troll-pattern signals

1. Shell-entity transfer — NOT PRESENT (as classically defined).
The patent did move from an operating company into an IP-holding entity, but both transferees are substantial, established entities, not anonymous single-purpose LLCs: Panasonic Intellectual Property Corporation of America is the U.S. IP subsidiary of a Fortune-Global-500 parent (2014-05-27), and Intertrust Technologies Corporation is a long-established Silicon Valley technology/licensing company (founded 1990; formerly NASDAQ-listed; taken private in 2016). No "[not retrieved]" name suffix like "Ventures/Holdings LLC," no registered-agent-service address, no single-member Delaware shell is evidenced. There is no evidence in this chain of the classic shell pattern. (Caveat: because I could not retrieve the recorded addresses, I cannot positively rule out an agent address — but nothing in the record supports the shell call, so I do not make it.)

2. Known asserter in the chain — PRESENT (moderate strength).
The chain terminates at Intertrust Technologies Corporation (2016-06-27 assignment). Intertrust is a known patent licensor with a substantial assertion history and is broadly catalogued in the patent-licensing ecosystem (its portfolio underpins the "trusted computing"/DRM field; it has been a repeat plaintiff — e.g., its high-profile litigation campaigns against major handset/PC vendors). It is not on the specific list named in the prompt (Acacia, Marathon, IV, IPNav, Wi-LAN, Conversant, Vringo, Pendrell, Innovatio, MPHJ, Lumen View, Round Rock, DGC, Spangenberg), so I rate this a moderate, not top-tier, known-asserter match — a well-known licensing/assertion entity rather than a pure play troll. Unified Patents' own portal entry for US-6463413-B1 lists the assignee as Intertrust Technologies Corp, corroborating the end of chain. Because the patent expired 2019-04-20, no live assertion of this patent is possible today.

3. Repeat correspondent across the chain — UNCLEAR / UNRETRIEVABLE.
This is the single most important signal I could not test: I was unable to retrieve the correspondent of record for any of the six entries, so I cannot say whether one attorney/firm ran multiple links. I am explicitly not inferring a repeat correspondent from the entity names. Anyone continuing this analysis should run the six records through https://assignmentcenter.uspto.gov/ and compare correspondent fields — that is the highest-value open check.

4. Cascading transfers — PARTIALLY PRESENT (weak).
Two title transfers occurred in roughly two years: 2014-05-27 (Panasonic → Panasonic IP Corp of America) and 2016-06-27 (Panasonic IP Corp of America → Intertrust) — an interval of ~25 months, just outside the "<24 months" formulation in the prompt, and the first leg is an internal reorg, not a third-party hop. There is no run of chained, unrelated assignee LLCs, and I have no evidence that the transferees share a correspondent address or common principals. Net: a two-step corporate-consolidation-then-disposition sequence, weak as an NPE tell.

5. Pre-litigation transfer — UNCLEAR.
The only litigation pointer on the Google Patents page is D. Del. 1:17-cv-01484 (filed ~2017-10), which — per the earlier section of this analysis — resolves to Nuance Communications v. MModal and shows no authoritative link to US 6,463,413. If a suit had been filed against this patent, the 2016-06-27 acquisition would sit ~4–16 months before it, straddling the 6-month test. I cannot make the call on an unverified docket. Additionally, the patent expired 2019-04-20, so any assertion window has closed. Mark unclear, leaning not established.

6. Bankruptcy fire-sale — NOT PRESENT.
Matsushita/Panasonic did not file Chapter 7/11; the 2014–2016 transfers are a corporate reorganization followed by a portfolio disposition, not a distress sale. No bankruptcy docket or §363 sale is evidenced.

7. Privateering — UNCLEAR, leaning plausible-but-unproven.
On its face this fits the privateering shape: an operating company (Panasonic) moving assets to a licensing entity (Intertrust) that monetizes them. But there is no evidence in the record — no SEC filing, no press release, no litigation pleading surfaced in this pass — that Intertrust asserted this patent on Panasonic's behalf against Panasonic competitors. Per the operating rules I do not upgrade naming/symmetry to a finding. Mark unclear.

8. Defensive aggregator — NOT PRESENT.
The chain does not terminate at RPX, AST, LOT Network, Unified Patents, or OIN. It terminates at a for-profit licensing company; the patent was not neutralized by defensive aggregation.


Verdict

NPE — moderate confidence.

One strong signal (signal 2: the chain terminates at Intertrust Technologies Corporation via the 2016-06-27 assignment — an established patent-licensing/assertion entity, not a product competitor of the original owner) plus one weak signal (signal 4: the 2014-05-27 → 2016-06-27 two-step transfer out of the Panasonic group within ~25 months). The chain does not exhibit the classic anonymous-shell pattern (signal 1 absent) and does not end at a defensive aggregator (signal 8 absent), so this is not high confidence. The verdict is additionally constrained by my inability to retrieve reel/frame or correspondent data for any entry — the repeat-correspondent signal (3), the strongest single NPE tell when it appears, is untestable on the present record. Note also that because the patent expired 2019-04-20, the current owner cannot assert it; any NPE characterization is historical.

Verify at: USPTO Assignment Center — https://assignmentcenter.uspto.gov/ (search patent number 6463413); legacy mirror — https://assignment.uspto.gov/patent/index.html. Cross-check the six entries above for reel/frame and correspondent.


Contradictions / corrections to the earlier section

  • The earlier section's assignment chain (Matsushita → Panasonic IP Corp of America, 2014-05-27 → Intertrust, 2016-06-27; security interest to Origin Future Energy, 2020-03-18; release, 2023-02-14) is fully consistent with the legal-events record I re-examined. No contradiction.
  • I add one clarification the earlier section only implied: the 2014-05-27 leg is an internal Panasonic reorganization (Panasonic Corp → its own U.S. IP-holding subsidiary), and the 2016-06-27 leg is the first transfer outside the Panasonic group. The earlier section labeled 2014 as "Matsushita Electric Industrial → Panasonic Intellectual Property Corporation of America," which is the same chain but skips the 2008 name change (Matsushita → Panasonic Corporation) that the record shows as the 2014 assignor's name.
  • The earlier section's caveat on the D. Del. 1:17-cv-01484 pointer stands; nothing in this ownership review rehabilitates it as an assertion of US 6,463,413.

Generated 9/25/2026, 4:48:59 AM

Prior art

Earlier patents, publications, and products that may anticipate or render the claims unpatentable.

✓ Generated

I'll verify this patent in the USPTO/patent databases and research the cited prior-art references before analyzing them.

Let me research the specific references most likely to bear on the independent claims — especially the server-side vocabulary generation and network-based speech references.

Prior-Art Analysis — US 6,463,413 B1

0. Patent identity confirmation (USPTO / mirror records)

The patent number 6463413 resolves only to US 6,463,413 B1, "Speech recognition training for small hardware devices" (Applebaum & Junqua; app. 09/295,276; filed 1999‑04‑20; issued 2002‑10‑08; expired 2019‑04‑20). Confirmed via the Google Patents full‑text record (fetched 2026‑09‑25), the USPTO‑derived mirror uspto.report/patent/grant/6463413, and the Unified Patents patent page portal.unifiedpatents.com/patents/patent/US-6463413-B1. No similar-number substitution was made. Note explicitly: a search for the string "6463413" also returns an unrelated OCLC # 6463413 (a 1978 U.S. DOE cement R&D report) and an SMC air-filter part number 6463413 — neither is the patent and both are disregarded.

Caveat / flag. I could not open the USPTO Patent Full‑Text search interface (patft/PatentCenter) directly in this session; the bibliographic data and citation list below are taken from the patent's own front‑page record as mirrored, which is authoritative for what the examiner cited. For the third‑party reference bodies I verified in full, I say so; where I am working from title + the patent's own characterization, I say so. This matters because §102 anticipation requires a single reference to disclose every claim limitation, arranged as claimed — a determination that normally needs the reference's full text.


1. Legal framework applied

  • US 6,463,413 has a 1999‑04‑20 filing/priority date, so pre‑AIA 35 U.S.C. § 102 governs.
  • A printed publication or patent published/issued more than one year before 1999‑04‑20 (i.e., before 1998‑04‑20) is available under § 102(b).
  • References issued between 1998‑04‑20 and the filing date, or US patents granted on earlier‑filed applications, are available under § 102(a) and/or § 102(e).
  • The four independent claims are 1, 11, 22, 32. Their common novel element is the distributed split: (i) a first device (generic / PDA / cell handset) converts training data into an intermediate representation; (ii) the intermediate representation is sent over a network to a second device; (iii) the second device builds the reference model; (iv) the model is sent back and stored in a lexicon on the first device.

Consequence for the §102 analysis: the 22 cited references are overwhelmingly single‑device training techniques or server‑side directory‑assistance systems. No single cited reference discloses the complete two‑device loop, so none is a clean §102 anticipator of claims 1/11/22/32. They are much better characterized as §103 (obviousness) art, and as §102 art against dependent claims. I map them accordingly below rather than over‑claiming anticipation.


2. The 22 examiner/third‑party patent citations (front‑page record)

Dates are as recorded on the front page (issue date / filing‑priority date → §102(b) if issued before 1998‑04‑20).

# Patent Issue date Filed/priority Assignee (record) Title §102 relevance to '413
1 US 4,754,326 1988‑06‑28 1983‑10‑25 Keycom Electronic Publishing Method and apparatus for assisting user of information retrieval systems §102(b). Background for user‑interactive info retrieval (address‑book/telephone‑lookup context of Fig. 1). Not directed to speech‑model training. Anticipates no claim.
2 US 4,751,737 1988‑06‑14 1985‑11‑06 Motorola, Inc. Template generation method in a speech recognition system §102(b). Verified full text. Generates word templates by averaging multiple training tokens with dynamic‑time‑warping alignment, minimizing memory. Closest art to claims 9–10 / 20–21 / 30–31 (multiple repetitions → alignment → averaged model) and the frame/spectral data of claims 4–5 / 17–18 / 27–28. Single device → cannot anticipate claims 1/11/22/32.
3 US 4,829,577 1989‑05‑09 1986‑03‑25 IBM Speech recognition method §102(b). Markov‑model recognition with alignment/adaptation. Background to claims 8 / 19 / 29 (HMM decoding). Anticipates no independent claim.
4 US 4,903,305 1990‑02‑20 1986‑05‑12 Dragon Systems, Inc. Method for representing word models for use in speech recognition §102(b). Word‑model representation. Background to claims 6 / 14 / 24 (model storage/lexicon).
5 US 5,850,627 1998‑12‑15 1992‑11‑13 Dragon Systems (now Nuance) Apparatuses and methods for training and operating speech recognition systems §102(a)/(e) (issued after 1998‑04‑20). Broad training + operating disclosure. Background to the training‑module subject matter of claims 7–10 / 15–21 / 25–31; single‑device.
6 US 5,497,447 1996‑03‑05 1993‑03‑08 IBM Speech coding apparatus having acoustic prototype vectors generated by tying to elementary models and clustering around reference vectors §102(b). Generation of prototype/reference vectors by clustering. Background to claims 4–5, 10 / 17–18, 21 / 27–28, 31 (parameter vectors; reference‑vector + variance construction).
7 US 5,488,652 1996‑01‑30 1994‑04‑14 Northern Telecom (now Volt Delta) Method and apparatus for training speech recognition algorithms for directory assistance applications §102(b). Verified full text. Prompts callers, recognizes, releases numbers, and uses the released numbers to refine/retrain the recognizer server‑side from cepstral feature vectors and HMM likelihoods. Best §102/§103 art for the server‑side training half of claim 1 and for claims 3–5, 8. Does not disclose the client sending an intermediate representation or receiving the model back into a client lexicon.
8 US 5,749,072 1998‑05‑05 1994‑06‑03 Motorola, Inc. Communications device responsive to spoken commands and methods of using same §102(b). Communications device with spoken‑command recognition. Background to the handset setting of claim 22; no distributed training disclosed.
9 US 5,477,511 1995‑12‑19 1994‑07‑13 Englehardt, C. Duane Portable documentation system §102(b). Portable device. Background only to the portability aspect of claims 11 / 22; no speech‑model training.
10 US 5,854,997 1998‑12‑29 1994‑09‑07 Hitachi, Ltd. Electronic interpreter utilizing linked sets of sentences §102(a)/(e). Handheld interpreter. Background to claims 11 / 22; unrelated to distributed training.
11 US 5,864,810 1999‑01‑26 1995‑01‑20 SRI International Method and apparatus for speech recognition adapted to an individual speaker §102(a)/(e). Speaker adaptation of HMMs. Background to claims 6, 9–10 / 14, 20–21 / 24, 30–31 (adapting/creating models).
12 US 5,715,367 1998‑02‑03 1995‑01‑23 Dragon Systems Apparatuses and methods for developing and using models for speech recognition §102(b). Model development. Background to claims 7–10 / 15–21 / 25–31.
13 US 6,070,140 2000‑05‑30 1995‑06‑05 Tran, Bao Q. Speech recognizer §102(a)/(b) (priority 1995). Could not verify full text. Because it was examiner‑cited and post‑dates the '413 in issue but not in priority, it is a candidate for claim 1 / 32 if it discloses networked/distributed training or remote lexicon updating — flag for verification.
14 US 5,822,728 1998‑10‑13 1995‑09‑08 Matsushita Electric Industrial Multistage word recognizer based on reliably detected phoneme similarity regions §102(b). Expressly incorporated by reference into '413 (Morin et al.). Background to claims 4, 8 / 17, 19 / 27, 29 (phoneme‑similarity speech representation).
15 US 5,825,977 1998‑10‑20 1995‑09‑08 Morin, Philippe R. (Matsushita) Word hypothesizer based on reliably detected phoneme similarity regions §102(b). Incorporated by reference. Background to claim 8 / 19 / 29 phoneme modeling.
16 US 5,684,925 1997‑11‑04 1995‑09‑08 Matsushita Electric Industrial Speech representation by feature‑based word prototypes comprising phoneme targets having reliable high similarity §102(b). Incorporated by reference. Background to claims 4, 6 / 17, 14 / 27, 24 (feature‑based word prototypes/representation).
17 US 5,884,262 1999‑03‑16 1996‑03‑28 Bell Atlantic Network Services (now Verizon) Computer network audio access and conversion system §102(a)/(e). Closest "network" reference. Uses a computer network to deliver/convert audio for speech access. Potentially relevant to the "interconnected via a network" limitation of claims 1 / 11 / 22 / 32; I could not verify that it discloses training‑model generation on a server returned to a client lexicon. Flag for verification — it is the single best §102/§103 candidate against the network‑architecture element.
18 US 5,806,030 1998‑09‑08 1996‑05‑06 Matsushita Electric Industrial Low complexity, high accuracy clustering method for speech recognizer §102(b). Clustering method. Background to claims 10 / 21 / 31 (variance/cluster‑based model construction).
19 US 6,055,498 2000‑04‑25 1996‑10‑02 SRI International Method and apparatus for automatic text‑independent grading of pronunciation for language instruction §102(e). Frames audio into features and scores pronunciation. Background to claims 3–5 / 17–18 / 27–28 (audio → parameter vectors).
20 US 5,839,107 1998‑11‑17 1996‑11‑29 Northern Telecom (now Avaya) Method and apparatus for automatically generating a speech recognition vocabulary from a white pages listing §102(b). Verified full text. Automatically generates a speech‑recognition vocabulary / pronunciations (orthographies) from a text listing via a heuristics model. The best §102/§103 art for the text‑input path — claims 2 / 13 / 23 (alphanumeric text as training data → symbol/pronunciation sequence) and claims 7 / 15 / 25 (phoneticizer/trainer producing pronunciations). Does not disclose returning models to a client device lexicon.
21 US 5,950,157 1999‑09‑07 1997‑02‑28 SRI International Method for establishing handset‑dependent normalizing models for speaker recognition §102(a)/(e). Handset‑dependent models. Background to claims 6 / 14 / 24 (speaker/handset‑dependent model databases) and to the handset context of claim 22.
22 US 6,266,642 B1 2001‑07‑24 1999‑01‑29 Sony Corporation Method and portable apparatus for performing spoken language translation §102(e) only (US patent granted on a pre‑filing application). Portable‑apparatus speech processing. Background to the "small hardware device" premise; could not verify any distributed training/return‑to‑lexicon disclosure.

3. "Family Cites Families" references (3) — cited against the EP/DE family members

These appear on the front page as family citations and are directly on point for the text‑to‑model and speaker‑model aspects:

Patent Issue date Filed Assignee Title §102 relevance
US 5,054,082 1991‑10‑01 1988‑06‑30 Motorola, Inc. Method and apparatus for programming devices to recognize voice commands §102(b). Programming a device to recognize new voice commands — closer than most to the "add words to the lexicon" object of the '413 (claims 1, 11, 22). But it is local/device‑resident programming, not client↔server.
US 5,212,730 1993‑05‑18 1991‑07‑01 Texas Instruments Voice recognition of proper names using text‑derived recognition models §102(b). Highest‑value text‑path art. Builds recognition models from text — maps onto claims 2 / 13 / 23 (alphanumeric text → symbol sequence) and the phoneticizer/pronunciation‑generation of claims 7 / 15 / 25. Consider with US 5,839,107 for §103 against the text‑path dependents.
US 5,732,187 1998‑03‑24 1993‑09‑27 Texas Instruments Speaker‑dependent speech recognition using speaker‑independent models §102(b). Maps onto claims 6 / 14 / 24 (a database of speaker‑independent reference models used to produce the stored model).

4. Non‑patent literature citations (3)

All three are the inventors' own phoneme‑similarity work (relevant as §102(a)/(b) printed publications, and notable because they are authored by the inventors, i.e., arguably their own prior work):

  1. Applebaum, T.H., P. Morin & B.A. Hanson, "A Phoneme‑Similarity Based ASR Front‑End," 1996, vol. 1, pp. 33–36.
  2. Morin, P., T.H. Applebaum, R. Bowman, Y. Zhao & J.-C. Junqua, "Robust and Compact Multilingual Word Recognizers Using Features Extracted From a Phoneme Similarity Front‑End," 1998.
  3. Morin, P. & T.H. Applebaum, "Word Hypothesizer Based on Reliably Detected Phoneme Similarity Regions," 1995, pp. 897–900.

§102 relevance: front‑end feature extraction (short‑term spectral representation) → claims 4–5 / 17–18 / 27–28, and phoneme‑similarity representation → claims 8 / 19 / 29. None discloses the distributed client‑server architecture.


5. Bottom line — most relevant §102 prior art

Against the independent claims (1, 11, 22, 32): no cited reference discloses all elements. The distinguishing element — client sends an intermediate representation over a network, server builds the model, server returns it to the client lexicon — is absent from every cited reference I verified. The two candidates warranting full‑text pull before any §102 assertion would be made are:

  • US 5,884,262 (Bell Atlantic — Computer network audio access and conversion system) — the only cited reference built around a network delivery architecture. Unverified on whether it trains/returns models.
  • US 6,070,140 (Tran — Speech recognizer, examiner‑cited) — unverified; examiner citation gives it elevated weight as a possible primary reference.

Against the dependent claims, the most relevant §102 references are:

  • Text/text‑to‑pronunciation path (claims 2, 7, 13, 15, 23, 25): US 5,839,107 (white‑pages vocabulary/pronunciation generation) and US 5,212,730 (text‑derived recognition models).
  • Audio → parameter‑vector path (claims 3–5, 17–18, 27–28): US 4,751,737, US 5,488,652, US 6,055,498.
  • HMM decoding / phonetic transcription (claims 8, 19, 29): US 4,829,577, US 5,488,652, US 5,864,810; plus incorporated‑by‑reference US 5,684,925 / 5,822,728 / 5,825,977.
  • Multi‑repetition → alignment → mean/variance model (claims 9–10, 20–21, 30–31): US 4,751,737 (strong — multiple tokens, time‑alignment, averaging) and US 5,497,447 (prototype/reference‑vector clustering).
  • Speaker‑independent model database (claims 6, 14, 24): US 5,732,187, US 5,950,157, US 5,864,810.
  • "Add words to a device" concept (device programming): US 5,054,082.

Practical conclusion: the cited art supports at most a §103 obviousness challenge to the independent claims (e.g., server‑side training of US 5,488,652 or US 5,839,107 combined with a network delivery system such as US 5,884,262), and possible §102 anticipation of individual dependent claims. It does not contain a single §102 reference that anticipates claims 1, 11, 22, or 32 as written. Treat the two flagged references (US 5,884,262 and US 6,070,140) as the priority items for full‑text retrieval; I could not verify their disclosures in this session and I am not asserting any conclusion about them.

Generated 9/25/2026, 4:49:09 AM

Obviousness

Combinations of prior art that suggest the claimed invention would have been obvious under 35 U.S.C. § 103.

✓ Generated

I'll ground the key prior-art references before assembling the § 103 analysis. Let me pull the cited references' disclosures.

Let me ground the remaining prominent cited references.

Obviousness Analysis — US 6,463,413 B1 under 35 U.S.C. § 103

Builds on the prior summary. The biblio table, abstract, and claim overview were generated earlier and are not repeated. This section assumes them and focuses on the § 103 question.

Scope note (important): Because the application was filed 1999-04-20, the pre-AIA version of § 103 governs, with prior art measured under pre-AIA §§ 102(a)/(b)/(e). I used only the references appearing in the "Prior Art" portions of the patent record — the 22 examiner citations, the 3 non-patent citations, and the 3 family citations (from the EP/DE sibling prosecution). I verified actual text for five references by search (US 5,488,652; 5,839,107; 5,884,262; 5,212,730; 5,864,810). The remainder I can only characterize at title/claim-category level, and I flag every such instance rather than asserting disclosure I have not read. Search budget was exhausted before I could pull the full text of US 4,751,737, 4,903,305, 5,850,627, 5,732,187, 5,749,072 and others — treat those mappings as provisional.


1. The prior-art inventory and its § 102 status

Ref Date of issue § 102 category Verified? Core teaching relied on
US 5,488,652 (Bielby, Northern Telecom) 1996-01-30 102(b) Yes Derives cepstral feature vectors from prompted caller speech; stores speech-signal representations in call records; an off-line processor computes HMM/prior parameters from labelled tokens and downloads the modified recognition-algorithm parameters to memory accessible by the on-line processor
US 5,884,262 (Wise, Bell Atlantic) 1999-03-16 102(a)/(e) Yes Thin-client (ordinary telephone) ↔ network server architecture; heavy transformation (text-to-speech, parsing, format conversion) done server-side; "voice recognition engine" and "speech-to-text converter" located at the network server
US 5,212,730 (Picone, TI) 1993-05-18 102(b) Yes Text-derived recognition models: from typed name-text alone, generate multiple alternative phonetic sequences and construct HMM recognition models via an HMM model generator + phonetic model library; stored in an HMM recognition model database
US 5,864,810 (Digalakis, SRI) 1999-01-26 102(a)/(e) Yes Adapts speaker-independent models into speaker-adapted models using a small amount of adaptation data; Gaussian mixture densities with stored means/variances; Baum-Welch/EM re-estimation
US 5,839,107 (Gupta/Sabourin, Northern Telecom) 1998-11-17 102(a)/(e) Yes Automatically generates a recognition vocabulary from a listing by building orthographies, then phonemic and acoustic transcriptions — server-side vocabulary creation without studio recordings
US 4,751,737 (Gerson, Motorola) 1988-06-14 102(b) No Template generation in a speech recognition system (title-level only)
US 4,903,305 (Dragon) 1990-02-20 102(b) No Representing word models for use in speech recognition (title-level)
US 5,850,627 / 5,715,367 (Dragon) 1998-12-15 / 1998-02-03 102(a)/(e) No Training and operating speech recognition systems; developing/using models (title-level)
US 5,732,187 (TI) 1998-03-24 102(b) No Speaker-dependent recognition using speaker-independent models (title-level)
US 5,749,072 (Motorola) 1998-05-05 102(b) No Communications device responsive to spoken commands (title-level)
US 5,475,751 (Englehardt); 4,754,326 (Keycom) 1995-12-19; 1988-06-28 102(b) No Portable documentation system; information-retrieval user assistance (title-level)
Applebaum/Morin NPL (1995, 1996, 1998) pre-filing 102(b) printed pubs n/a Phoneme-similarity front-end producing compact feature representations; word hypothesizer on reliably detected phoneme similarity regions
US 6,055,498; 6,070,140; 6,266,642 issued 2000–2001, filed 1996-10-02 / 1995-06-05 / 1999-01-29 102(e) (filed before 1999-04-20) No SRI pronunciation grading; Tran speech recognizer; Sony spoken-language translation

Two structural observations about this record:

  • The examiner's citations are concentrated on what a speech model is and how it is built (Matsushita's own phoneme-similarity family, Dragon's word models, SRI/TI adaptation) and on telephony-side training and vocabulary generation (Northern Telecom, Bell Atlantic). They do not include a reference squarely on "client extracts features and ships them to a server that builds the model," which is the patent's point of novelty.
  • Three references (US 6,055,498, 6,070,140, 6,266,642) qualify only as § 102(e) art, so they can be used in a § 103 combination but must be shown to be "by another" and to have been filed on the earlier date.

2. Claim 1 / Claim 32: the primary combination

Proposed combination: US 5,488,652 (Bielby) as primary, in view of US 5,884,262 (Wise), further in view of US 5,864,810 (Digalakis).

Claim 1 element Where taught
Speech recognizer on a first computing device Bielby's on-line processor/recognizer; Wise's voice recognition engine; Motorola US 5,749,072 (portable device, title-level)
Receives speech training data → intermediate representation Bielby: "Process Received Speech Signal to Derive Representation"; "Derive Cepstral and Equalized Cepstral Feature Vectors." Applebaum/Morin NPL: phoneme-similarity feature vectors
Communicates the intermediate representation to a second computing device over a network Bielby: speech-signal representations are stored in call records that the off-line processor reads and writes back to the on-line processor's memory. Wise: explicit thin-client ↔ network-server split with the heavy transformation on the server
Speech model server on the second device generates the model from the IR Bielby: off-line processor "uses the labelled speech tokens to refine the training" and "calculate hidden Markov model parameters." Digalakis: derives SA models from SI models. Picone (US 5,212,730): HMM model generator constructs recognition models and stores them in an HMM database
Model communicated back to the first device Bielby: "download the modified speech recognition algorithm parameters to memory accessible by the on-line processor"
Lexicon on the first device storing the returned model Bielby's write-accessible on-line model parameters; Picone's HMM recognition model database

Why a POSITA would combine them. Bielby supplies the two-stage, parameter-refinement architecture and expressly frames the training step (not recognition) as the costly one — 20,000 labelled tokens and "several weeks of a skilled speech scientist's time" — and locates it off-line with a parameter download to the recognizer. Wise supplies the reason and the mechanism to push that off-line stage across a network: it demonstrates a functionally thin terminal (an ordinary telephone) relying on a remote server for exactly the conversions the terminal cannot afford locally, and it shows the conversion being done on user command traffic routed between client and server. A POSITA seeking to give a PDA or handset new words without a speech scientist would take Bielby's off-line trainer and Wise's client-server split and put the trainer on the server. Digalakis supplies the further teaching that the adaptation step can operate on a small amount of data and produces models by transformation rather than from scratch — which is what makes shipping compact feature data (rather than raw audio) a sensible design choice.

KSR factors: the improvement is a rearrangement of known elements (recognizer, feature extractor, model trainer, network link, lexicon) with each element performing its known function; the design incentive is stated on the face of the patent's own background (limited memory and processing power in PDAs/handsets) and in Bielby; the bandwidth saving from transmitting parameters instead of audio is a predictable, recognized engineering tradeoff.


3. Claim 11 (PDA) and Claim 22 (handset)

  • Claim 11 adds only device identity plus "input means." Combine the § 2 combination with US 4,754,326 (Keycom, information-retrieval user assistance) or US 5,475,751 (Englehardt, portable documentation system) for a portable computing device with user data entry. The PDA form factor was notoriously well known by 1999; the Federal Circuit's KSR "predictable variation" rationale covers substituting one known portable computing platform for another.
  • Claim 22 adds handset identity plus "input means." US 5,749,072 (Motorola, "Communications device responsive to spoken commands") is the on-point cited reference for a portable communications device carrying a recognizer; US 5,884,262's telephone interface supplies the network side.
  • Claims 12–13 (stylus + handwriting recognition → alphanumeric → symbol sequence). This is the weakest link in the record. No reference in the cited list discloses a stylus/display-pad/handwriting-recognition front end. A challenger would need art outside the cited record (digitizer/handwriting front ends were commercially ubiquitous by 1999), so on this record claims 12–13 are the least vulnerable. Note, however, that the handwriting module is invoked only as a source of alphanumeric text; the technical contribution of claim 13 is the symbol-sequence intermediate representation, which Picone's and Gupta's text-to-model pipelines both supply.
  • Claim 23 (keypad-authored alphanumeric data). Combine US 5,212,730 and US 5,839,107 — both generate recognition models/dictionaries from typed text with no spoken enrollment.

4. Dependent claims: secondary combinations

Claim group Combination Rationale
2, 13, 23 (alphanumeric text as training data; sequence of symbols as IR) US 5,212,730 + US 5,839,107 Both create recognition models from text; Gupta explicitly produces orthographies and then phonemic and acoustic transcriptions
3–5, 17–18, 27–28 (audio digitized to a parameter vector; PCM, μ-law, filter bank, LSF, cepstral) US 5,488,652 (cepstral/equalized-cepstral vectors) + Applebaum/Morin NPL (phoneme-similarity front-end) + US 5,497,447 (IBM, acoustic prototype vectors, title-level) The enumerated parameter types are the ordinary feature vocabulary of the 1990s; the claim language is a list of alternatives
6, 14, 24 (server-side database of speaker-independent models; lookup first) US 5,732,187 + US 5,864,810 + US 5,488,652 TI's title alone states the SI-model-to-SD-model path; Digalakis details SI models being stored and adapted; Bielby maintains a bank of HMM parameters
7, 15, 25 (phoneticizer → multiple phonetic transcriptions + model trainer) US 5,212,730 + Applebaum/Morin + Matsushita US 5,822,728 / 5,825,977 / 5,684,925 Picone is a near-perfect match: repeated text input generates different phonetic feature sequences (alternative pronunciations), which feed an HMM recognition-model generator. The Matsushita references are the inventors' own corporate prior art for the same feature front-end
8, 19, 29 (HMM phone-model database; decode parameter vectors into a phonetic transcription that serves as the model) US 4,903,305 + US 5,488,652 + US 5,850,627 / 5,715,367 + US 5,212,730 Bielby decodes cepstral feature vectors against cepstral HMMs and retains transcriptions; Picone's phonetic model library supplies the phone-model layer
9–10, 20–21, 30–31 (≥2 repetitions; align to a reference vector; mean and variance per parameter) US 5,864,810 + US 5,488,652 + US 5,850,627 Digalakis describes Gaussian mixture densities derived from training data with stored means/variances and re-estimation from small datasets; Bielby labels and accumulates repeated tokens to calculate HMM parameters. The mean/variance formulation is the textbook continuous-density HMM parameterization
32 (method) Same combination as claim 1 Purely a change of statutory category; the step sequence mirrors Bielby's process flow (derive representation → label → compute parameters → make parameters available to the recognizer) with Wise's network hop inserted

5. Motivation-to-combine, consolidated

  1. Stated problem + known solution in the field. The patent's own background concedes that cost sensitivity, fixed program memory, RAM, and processor speed in consumer devices, and the fact that "training … is more costly … than … the speech recognition process," were known. That concession supplies the design incentive without any hindsight reconstruction.
  2. Bielby's own architecture is the template. Separate the expensive trainer from the deployed recognizer; refine on stored parameter representations; download the resulting parameters into the recognizer's memory. The only change is where the trainer sits.
  3. Wise supplies the network hop and the thin-client reason. A network server performing conversions a terminal cannot do locally, on user request, over PSTN/Internet.
  4. Digalakis and TI US 5,732,187 supply the SI-model foundation, making the per-user training step a transformation of existing models from a compact data set rather than a full retrain — which is what makes transmitting features (rather than audio) both feasible and desirable.
  5. Picone and Gupta remove any argument that text-driven model creation was unpredictable, covering the text-path claims independently of any audio enrollment.
  6. Predictable results. Transmitting a parameter sequence instead of a waveform is a straightforward bandwidth/quantization tradeoff; storing returned model parameters in a lexicon is the same operation Bielby performs with downloaded parameters.

6. Where the § 103 case is weakest — and what I cannot verify

  • The "communicate the intermediate representation to a second, user-owned computing device over a network" limitation has no clean single-reference disclosure in the cited record. Bielby's off-line processor is on the service provider's side of the same installation, not in a small autonomous consumer device that keeps its own lexicon. The obviousness case therefore rests on combination, not anticipation. I found no cited reference that anticipates claim 1 in all respects.
  • Claims 12–13 (stylus/handwriting front end) are unsupported by any cited reference; I read them as the most defensible claims on this record, though for reasons that are engineering-conventional rather than inventive.
  • Provisional mappings flag. For US 4,751,737, 4,903,305, 5,850,627, 5,715,367, 5,732,187, 5,749,072, 5,475,751, 4,754,326 and the three § 102(e) references, I am relying on titles and claim categories. My search budget ran out before full-text confirmation. If any of these turns out to disclose a client/server feature-extraction split, the analysis for claim 1 strengthens materially; if any is limited to a single-processor architecture, the claim-1 case rests more heavily on Bielby + Wise alone.
  • No secondary considerations are in evidence. I have found no verified record of commercial success, licensing, or industry praise tied to this patent, and no file history to show whether the examiner considered the specific combination above. Issuance in 2002 with these references of record is not evidence of non-obviousness.
  • Practical relevance: the patent expired 2019-04-20 (per the earlier section), so any § 103 conclusion here is retrospective. It matters for historical/validity purposes and for the Intertrust portfolio, not for a live infringement defense.

Bottom line. On the cited record, claims 1, 11, 22 and 32 are, in my view, vulnerable to a § 103 challenge built on US 5,488,652 (Bielby) in view of US 5,884,262 (Wise), with US 5,864,810 (Digalakis) and/or US 5,732,187 supplying the SI-model angle; the text-path dependent claims fall to US 5,212,730 (Picone) in view of US 5,839,107 (Gupta); the phoneticizer/HMM dependent claims fall to Picone in view of the Dragon references and the Applebaum/Morin publications; and the mean/variance dependent claims fall to Digalakis in view of Bielby. The stylus/handwriting claims (12–13) are the exception on this particular record.

Generated 9/25/2026, 4:49:14 AM

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