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HUMAN AND MACHINE RECOGNITION OF NASAL CONSONANTS IN Abeer Alwan, Jeff Lo*, and Qifeng Zhu
 

Summary: HUMAN AND MACHINE RECOGNITION OF NASAL CONSONANTS IN
NOISE
Abeer Alwan, Jeff Lo*, and Qifeng Zhu
Department of Electrical Engineering, UCLA
Los Angeles, CA 90095
*NEC Electronics, Santa Clara, CA
ABSTRACT
The nasal consonants /m, n/ are often confused in the presence
of background noise. In addition, these consonants are difficult
to recognize reliably by machine. In this study, the perception of
the place of articulation for nasal consonants in adverse
conditions is examined through a series of perceptual
experiments. The experiments examined the effects of additive
white Gaussian noise (AWGN), and additive speech-shaped
noise on nasal place perception in CV syllables. Results show a
strong vowel-context effect. For example, it appears that the role
of the formant transitions is more critical than that of the
murmur in signaling place for /Ca/ and /Cu/ syllables while both
the murmur and formant transitions appear to be important in
signaling place for /Ci/ syllables. A Hidden Markov Model

  

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

 

Collections: Computer Technologies and Information Sciences