The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.

The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.

Date of Patent:
Jun. 28, 2016

Filed:

Sep. 30, 2014
Applicant:

Apple Inc., Cupertino, CA (US);

Inventors:

Harvey D. Thornburg, Cupertino, CA (US);

Charles P. Clark, Mountain View, CA (US);

Assignee:

Apple Inc., Cupertino, CA (US);

Attorney:
Primary Examiner:
Assistant Examiner:
Int. Cl.
CPC ...
G10L 15/20 (2006.01); G10L 19/04 (2013.01); G10L 25/84 (2013.01);
U.S. Cl.
CPC ...
G10L 25/84 (2013.01); G10L 15/20 (2013.01); G10L 19/04 (2013.01);
Abstract

Method of detecting voice activity starts with by generating probabilistic models that respectively model features of speech dynamically over time. Probabilistic models may model each feature dependent on a past feature and a current state. Features of speech may include a nonstationary signal presence feature, a periodicity feature, and a sparsity feature. Noise suppressor may then perform noise suppression on an acoustic signal to generate a nonstationary signal presence signal and a noise suppressed acoustic signal. An LPC module may then perform residual analysis on the noise suppressed data signal to generate a periodicity signal and a sparsity signal. Inference generator receives the probabilistic models and receives, in real-time, nonstationary signal presence signal, periodicity signal, and sparsity signal. Inference generator may then generate in real time an estimate of voice activity based on the probabilistic models, nonstationary signal presence signal, periodicity signal, and sparsity signal. Other embodiments are also described.


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