Vowel non-vowel based spectral warping and time scale modification for improvement in children’s ASR

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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 languageEnglish
Title of host publicationIEEE International Conference on Acoustics, Speech and Signal Processing
PublisherIEEE
Pages6983-6987
Number of pages5
Volume2021-June
ISBN (Electronic)978-1-7281-7605-5
DOIs
Publication statusPublished - 2021
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech and Signal Processing - Toronto, Canada
Duration: 6 Jun 202111 Jun 2021

Publication series

NameProceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing
ISSN (Print)1520-6149
ISSN (Electronic)2379-190X

Conference

ConferenceIEEE International Conference on Acoustics, Speech and Signal Processing
Abbreviated titleICASSP
Country/TerritoryCanada
CityToronto
Period06/06/202111/06/2021

Keywords

  • Spectral warping
  • vowel
  • non-vowel
  • TSM
  • children speech recognition

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