This work is motivated by our earlier study which shows that on explicit pitch normalization the children’s speech recognition performance on the adults’ speech trained models improves as a result of reduction in the pitch-dependent distortions in the spectral envelope. In this paper, we study the role of spectral smoothing in context of children’s speech recognition. The spectral smoothing has been effected in the feature domain by two approaches viz., modification of bandwidth of the filters in the filterbank and cepstral truncation. In conjunction, both approaches give significant improvement in the children’s speech recognition performance with 57% relative improvement over the baseline. Also, when combined with the widely used vocal tract length normalization (VTLN), these spectral smoothing approaches result in an additional 25% relative improvement over the VTLN performance for children’s speech recognition on the adults’ speech trained models.
Bibliographic reference. Ghai, Shweta / Sinha, Rohit (2009): "Exploring the role of spectral smoothing in context of children's speech recognition", In INTERSPEECH-2009, 1607-1610.