Abstract
Acoustic differences between children’s and adults’ speech causes the degradation in the automatic speech recognition system performance when system trained on adults’ speech and tested on children’s speech. The key acoustic mismatch factors are formant, speaking rate, and pitch. In this paper, we proposed a linear prediction based spectral warping method by using the knowledge of vowel and non-vowel regions in speech signals to mitigate the formant frequencies differences between child and adult speakers. The proposed method gives 31% relative improvement over the baseline system. We have also investigated time scale modification using RTISILA and SOLAFS algorithms and found that our proposed method performs better. Combining the proposed method with RTISILA and SOLAFS results in a further error rate reduction. The final combined system gives 49% relative improvement compared to the baseline system.
Original language | English |
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Title of host publication | IEEE International Conference on Acoustics, Speech and Signal Processing |
Publisher | IEEE |
Pages | 6983-6987 |
Number of pages | 5 |
Volume | 2021-June |
ISBN (Electronic) | 978-1-7281-7605-5 |
DOIs | |
Publication status | Published - 2021 |
MoE publication type | A4 Conference publication |
Event | IEEE International Conference on Acoustics, Speech, and Signal Processing - Virtua, Online, Toronto, Canada Duration: 6 Jun 2021 → 11 Jun 2021 |
Publication series
Name | Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing |
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ISSN (Print) | 1520-6149 |
ISSN (Electronic) | 2379-190X |
Conference
Conference | IEEE International Conference on Acoustics, Speech, and Signal Processing |
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Abbreviated title | ICASSP |
Country/Territory | Canada |
City | Toronto |
Period | 06/06/2021 → 11/06/2021 |
Keywords
- Spectral warping
- vowel
- non-vowel
- TSM
- children speech recognition