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Robust automatic speech recognition for children ...
Gurunath Shivakumar, Prashanth
. - : University of Southern California Digital Library (USC.DL), 2015
Abstract:
Developing a robust ASR system for children is a challenging task because of increased variability in acoustic and linguistic correlates as function of young age. The acoustic variability is mainly due to the developmental changes associated with vocal tract growth. On the linguistic side, the variability is associated with limited knowledge of vocabulary, pronunciations and other linguistic constructs. ❧ This study aims to develop a more robust acoustic modeling framework through a better front-end speech processing, pronunciation modeling, duration modeling, subword modeling for more accurate children's speech recognition. The thesis study focuses on the comprehensive tests of pre-existing methods in acoustic modeling for children's speech recognition. The results are presented as a function of age to study the effect of age on the performance. The inter-database effects are taken into account by using multiple databases of children's speech. Pronunciation modeling is introduced for children's speech. The ...
Keyword:
acoustic adaptation
;
acoustic modeling
;
automatic speech recognition
;
duration modeling
;
Electrical Engineering
;
front-end features
;
pronunciation modeling
;
subword modeling
URL:
https://dx.doi.org/10.25549/usctheses-c3-512162
https://digitallibrary.usc.edu/asset-management/2A3BF1LXARL4
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