Study of Formant Modification for Children ASR

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Abstract

The performance of automatic speech recognition systems for children’s speech is known to suffer from the large variation and mismatch in the acoustic and linguistic attributes between children’s and adults’ speech. One of the various identified sources of mismatch is the difference in formant frequencies between adults and children. In this paper, we propose a formant modification method to mitigate differences between adults’ and children’s speech and to improve the performance of ASR for children. The explored technique gives a relative 27% improvement in system performance compared to a hybrid DNN-HMM baseline. We also compare the system performance with related speaker adaptation methods like vocal tract length normalization (VTLN) and speaking rate adapta-
tion (SRA) and find that the proposed method gives improvements over them, as well. Combining the proposed method with VTLN and SRA results in a further reduction of WER. We also found that the proposed method performs well even
for noisy speech.
Original languageEnglish
Title of host publication2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
PublisherIEEE
Pages7429-7433
Number of pages5
ISBN (Electronic)978-1-5090-6631-5
ISBN (Print)978-1-5090-6632-2
DOIs
Publication statusPublished - May 2020
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech, and Signal Processing - Virtual conference, Barcelona, Spain
Duration: 4 May 20208 May 2020
Conference number: 45

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/TerritorySpain
CityBarcelona
Period04/05/202008/05/2020
OtherVirtual conference

Keywords

  • hildren speech recognition
  • Formant modification
  • DNN

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