Audyssey Laboratories, Inc.

Nathan Dahlin

Sunil Bharitkar

Ismael Hamad Nawfal

Chris Kyriakakis

Sunil Baritkar

A Voice Activity Detection (VAD) algorithm provides a simple binary signal indicating the presence or absence of speech in a microphone signal. The VAD algorithm includes a first step of noise suppression which both estimates and removes (i.e., filters) ambient noise from the microphone signal to create a filtered signal. The magnitude of the filtered signal is then compared to a threshold in order to produce a VAD output signal. The threshold is dynamic and may be derived either from the filtered signal itself, or from a noise spectrum estimate calculated by the noise suppression step.

System and method for performing voice activity detection

Methods, devices and computer program products facilitate the generation of high quality audio content. The audio content includes upper harmonics that are associated with a bass band of frequencies in order to enhance the perception of bass audio components that cannot be produced by the audio speakers. The upper harmonics are generated and processed in such a way that reduces the computational and memory requirements of the audio processing operations. The processed upper harmonics are combined with the original audio that are properly delayed to enhance the quality of the audio content. This Abstract is provided for the sole purpose of complying with the Abstract requirement rules that allow a reader to quickly ascertain the disclosed subject matter. Therefore, it is to be understood that it should not be used to interpret or limit the scope or the meaning of the claims.

Audio content enhancement using bandwidth extension techniques

A Dynamic Noise Compensation (DNC) telephone speech enhancement algorithm addresses the issue of environment noise on the listener end of a telephone call. A single microphone proximal to the listener provides a sample of near end ambient noise level and of near end speech. A Voice Activity Detector (VAD) detects the presence of near end (listener) speech. The DNC algorithm adjusts the far end incoming speech level based on the near end ambient noise and the VAD ensures that the near end listener speech does not effect the incoming speech level adjustment.

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Nathan Dahlin