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Automatic detection of the second subglottal resonance and its application to speaker normalizationa)
 

Summary: Automatic detection of the second subglottal resonance and its
application to speaker normalizationa)
Shizhen Wangb
Department of Electrical Engineering, University of California, Los Angeles, California 90095
Steven M. Lulich
Speech Communication Group, MIT, Cambridge, Massachusetts 02139
Abeer Alwan
Department of Electrical Engineering, University of California, Los Angeles, California 90095
Received 24 December 2008; revised 24 September 2009; accepted 25 September 2009
Speaker normalization typically focuses on inter-speaker variabilities of the supraglottal vocal
tract resonances, which constitute a major cause of spectral mismatch. Recent studies have shown
that the subglottal airways also affect spectral properties of speech sounds, and promising results
were reported using the subglottal resonances for speaker normalization. This paper proposes a
reliable algorithm to automatically estimate the second subglottal resonance Sg2 from speech
signals. The algorithm is calibrated on children's speech data with simultaneous accelerometer
recordings from which Sg2 frequencies can be directly measured. A cross-language study with
bilingual Spanish-English children is performed to investigate whether Sg2 frequencies are
independent of speech content and language. The study verifies that Sg2 is approximately constant
for a given speaker and thus can be a good candidate for limited data speaker normalization and
cross-language adaptation. A speaker normalization method using Sg2 is then presented. This

  

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

 

Collections: Computer Technologies and Information Sciences