System and method for multi-channel multi-feature speech/noise classification for noise suppression
First Claim
1. A method for noise estimation and filtering based on classifying an audio signal received at a noise suppression module via a plurality of input channels as speech or noise, the method comprising:
- measuring signal classification features for a frame of the audio signal input from each of the plurality of input channels;
generating a feature-based speech probability for each of the measured signal classification features of each of the plurality of input channels;
generating a combined speech probability for the measured signal classification features over the plurality of input channels using a probabilistic layered network model, wherein an additive model is used for a top layer of the probabilistic layered network model;
classifying the audio signal as speech or noise based on the combined speech probability; and
updating an initial noise estimate for each of the plurality of input channels using the combined speech probability.
1 Assignment
0 Petitions
Accused Products
Abstract
An architecture and framework for speech/noise classification of an audio signal using multiple features with multiple input channels (e.g., microphones) are provided. The architecture may be implemented with noise suppression in a multi-channel environment where noise suppression is based on an estimation of the noise spectrum. The noise spectrum is estimated using a model that classifies each time/frame and frequency component of a signal as speech or noise by applying a speech/noise probability function. The speech/noise probability function estimates a speech/noise probability for each frequency and time bin. A speech/noise classification estimate is obtained by fusing (e.g., combining) data across different input channels using a layered network model. Individual feature data acquired at each channel and/or from a beam-formed signal is mapped to a speech probability, which is combined through layers of the model into a final speech/noise classification for use in noise estimation and filtering processes for noise suppression.
27 Citations
28 Claims
-
1. A method for noise estimation and filtering based on classifying an audio signal received at a noise suppression module via a plurality of input channels as speech or noise, the method comprising:
-
measuring signal classification features for a frame of the audio signal input from each of the plurality of input channels; generating a feature-based speech probability for each of the measured signal classification features of each of the plurality of input channels; generating a combined speech probability for the measured signal classification features over the plurality of input channels using a probabilistic layered network model, wherein an additive model is used for a top layer of the probabilistic layered network model; classifying the audio signal as speech or noise based on the combined speech probability; and updating an initial noise estimate for each of the plurality of input channels using the combined speech probability. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19, 20, 21, 22, 23, 24, 25, 26, 27, 28)
-
Specification