Nuance Communications, Inc.

Daniel Almendro Barreda

Dushyant Sharma

Patrick A Naylor

Jose Lainez

Sridhar Pilli

Uwe Helmut Jost

Mahesh Godavarti

Diven Topiwala

Lisa Meredith

Jose E G Lainez

A system, method and computer program product are described for voice activity detection (VAD) within a digitally encoded bitstream. A parameter extraction module is configured to extract parameters from a sequence of coded frames from a digitally encoded bitstream containing speech. A VAD classifier is configured to operate with input of the digitally encoded bitstream to evaluate each coded frame based on bitstream coding parameter classification features to output a VAD decision indicative of whether or not speech is present in one or more of the coded frames.

Voice activity detection (VAD) for a coded speech bitstream without decoding

Embodiments included herein are directed towards a system and method for compressed domain language identification. Embodiments may include receiving a bitstream of a sequence of packets at one or more computing devices and classifying each packet into speech or non-speech based upon, at least in part, compressed domain voice activity detection (VAD). Embodiments may further include extracting a pseudo-cepstral representation from the speech detected packets and partially decoding without extracting a PCM format and generating a sequence of multi-frames, based upon, at least in part, the pseudo-cepstral representation. Embodiments may also include providing in real time the sequence of multi-frames to a deep neural network (DNN), wherein the DNN has been trained off-line for one or more desired target languages.

System and method for compressed domain language identification

The present disclosure is directed towards a method for discontinuous transmission ('DTX') bandwidth reduction. The method may include receiving, at a processor, a frame identified as speech and determining that the frame was mistakenly identified as speech based upon, at least in part, a voice activity detection algorithm. The method may further include labeling the frame as a silence indicator frame.

System and method to reduce transmission bandwidth via improved discontinuous transmission

The present disclosure is directed towards a process for estimating the signal to noise ratio of a speech signal. The process may include receiving, at a computing device, a speech signal having a bitstream and a signal-to-noise ratio ('SNR') associated therewith. The process may further include estimating the SNR directly from the bitstream or using a partial decoder that is configured to extract one or more parameters, the parameters including at least one of a fixed codebook gain, an adaptive codebook gain, a pitch lag, and a line spectral frequency ('LSF') coefficient.

System and method for compressed domain estimation of the signal to noise ratio of a coded speech signal

Typical textual prediction of voice data employs a predefined implementation arrangement of a single or multiple prediction sources. Using a predefined implementation arrangement of the prediction sources may not provide a good prediction performance in a consistent manner with variations in voice data quality. Prediction performance may be improved by employing adaptive textual prediction. According to at least one embodiment determining a configuration of a plurality of prediction sources, used for textual interpretation of the voice data, is determined based at least in part on one or more features associated with the voice data or one or more a-priori interpretations of the voice data. A textual output prediction of the voice data is then generated using the plurality of prediction sources according to the determined configuration. Employing an adaptive configuration of the text prediction sources facilitates providing more accurate text transcripts of the voice data.

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London, United Kingdom

Daniel Almendro Barreda