NDLI: Robust recognition of children's speech

Content Provider	IEEE Xplore Digital Library
Author	Potamianos, A. Narayanan, S.
Copyright Year	1993
Abstract	Developmental changes in speech production introduce age-dependent spectral and temporal variability in the speech signal produced by children. Such variabilities pose challenges for robust automatic recognition of children's speech. Through an analysis of age-related acoustic characteristics of children's speech in the context of automatic speech recognition (ASR), effects such as frequency scaling of spectral envelope parameters are demonstrated. Recognition experiments using acoustic models trained from adult speech and tested against speech from children of various ages clearly show performance degradation with decreasing age. On average, the word error rates are two to five times worse for children speech than for adult speech. Various techniques for improving ASR performance on children's speech are reported. A speaker normalization algorithm that combines frequency warping and model transformation is shown to reduce acoustic variability and significantly improve ASR performance for children speakers (by 25-45% under various model training and testing conditions). The use of age-dependent acoustic models further reduces word error rate by 10%. The potential of using piece-wise linear and phoneme-dependent frequency warping algorithms for reducing the variability in the acoustic feature space of children is also investigated.
Starting Page	603
Ending Page	616
Page Count	14
File Size	500594
File Format	PDF
ISSN	10636676
Volume Number	11
Issue Number	6
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2003-11-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Robustness Speech recognition Automatic speech recognition Frequency Speech analysis Acoustic testing Error analysis Loudspeakers Degradation Piecewise linear techniques
Content Type	Text
Resource Type	Article
Subject	Acoustics and Ultrasonics Electrical and Electronic Engineering Computer Vision and Pattern Recognition Software

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