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In this paper, the acoustic and linguistic characteristics of children speech are investigated in the context of automatic speech recognition. Acoustic variability is identi ed as a major hurdle in building high performance ASR applications for children. A simple speaker normalization algorithm combining frequency warping and spectral shaping introduced in 5 is shown to reduce acoustic variability and signi cantly improve recognition performance for children speakers (by 25{ 45%). Age-dependent acoustic modeling further reduces word error rate by 10%. Piece-wise linear and phoneme-dependent frequency warping algorithms are proposed for reducing acoustic mismatch between the children and adult acoustic spaces.
Potamianos et al. (Mon,) studied this question.