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VOICE ACTIVITY DETECTION USING HARMONIC FREQUENCY COMPONENTS IN LIKELIHOOD RATIO TEST
 

Summary: VOICE ACTIVITY DETECTION USING HARMONIC FREQUENCY
COMPONENTS IN LIKELIHOOD RATIO TEST
Lee Ngee Tan, Bengt J. Borgstrom and Abeer Alwan
Department of Electrical Engineering, University of California, Los Angeles
{tleengee, jonas, alwan}@ee.ucla.edu
ABSTRACT
This paper proposes a new statistical model-based likelihood
ratio test (LRT) VAD to obtain reliable speech / non-speech
decisions. In the proposed method, the likelihood ratio (LR)
is calculated differently for voiced frames, as opposed to
unvoiced frames: only DFT bins containing harmonic
spectral peaks are selected for LR computation. To evaluate
the new VAD's effectiveness in improving the noise-
robustness of ASR, its decisions are applied to pre-
processing techniques such as non-linear spectral
subtraction, minimum mean square error short-time spectral
amplitude estimator, and frame dropping. From the ASR
experiments conducted on the Aurora2 database, the
proposed harmonic frequency-based LRTs give better
results than conventional LRT-based VADs and the standard

  

Source: Alwan, Abeer - Electrical Engineering Department, University of California at Los Angeles

 

Collections: Computer Technologies and Information Sciences