US 10783899

A concise summary of US Patent 10,783,899, which is titled "Babble noise suppression," is provided below. There is no record of this patent in the CAFC 2026 dockets.

Title: Babble noise suppression

Assignee: Cerence Operating Company

Inventors: Simon Graf, Tobias Herbig, Markus Buck

Filing Date: November 18, 2016

Issue Date: September 22, 2020

Abstract: The patent describes systems and methods for suppressing noise in an audio signal that contains both foreground speech and background noise. Specifically, it targets "babble noise," which consists of speech from interfering speakers. The technology uses a "soft speech detector" to dynamically determine the likelihood that the user is speaking. This information is then used to control the level of noise suppression, reducing the babble noise while preserving the user's speech. The system also aims to create a more stationary background noise and reduce musical tone artifacts.

Overview of Independent Claims:

This patent has three independent claims: 1, 15, and 23.

Claim 1: This claim outlines a system for noise suppression. The core of this system is a "soft speech detector" that continuously estimates the probability of foreground speech being present in an audio signal. This probability is then used by a "noise suppressor" to dynamically calculate and apply spectral weighting coefficients to the audio signal. A key innovation is the use of a "dynamic noise overestimation factor," which is increased during speech pauses to more aggressively suppress background noise and decreased during speech activity to avoid distorting the desired speech.

Claim 15: This claim describes a method for noise suppression that mirrors the functionality of the system in Claim 1. It details the steps of dynamically determining a speech detection result (the likelihood of foreground speech), and then dynamically computing and applying spectral weighting coefficients based on this result to suppress background noise. The method also involves computing a dynamic noise overestimation factor based on the speech detection result to control the aggressiveness of the noise suppression.

Claim 23: This claim covers a non-transitory computer-readable medium. This medium stores a sequence of instructions that, when executed by a processor, cause the processor to perform the method of noise suppression detailed in Claim 15. This includes dynamically determining the likelihood of speech, computing spectral weighting coefficients based on that likelihood, and applying them to the audio signal. The method also includes using a dynamic noise overestimation factor to adjust the level of noise suppression based on whether speech is present.