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Studying the Effectiveness of Data Augmentation and Frequency-Domain Linear Prediction Coefficients in Children’s Speaker Verification Under Low-Resource Conditions

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Speech and Computer (SPECOM 2023)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 14339))

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Abstract

Developing an automatic speaker verification (ASV) system for children is extremely challenging due to the rarity of children’s speech corpora. To deal with data scarcity, we have developed an out-of-domain data augmentation technique in this work. For that purpose, we have resorted to pitch scaling, formant modification, time-scale modification, and voice-conversion of adults’ speech in order to render it acoustically similar to children’s speech. The children’s speech along with the modified and original adults’ data are then pooled into training. Furthermore, two complementary front-end features namely, Mel-frequency cepstral coefficients (MFCC) and frequency-domain linear prediction (FDLP) coefficients have been concatenated so as to simultaneously capture the spectral as well as temporal envelopes. The feature concatenation approach when combined with data augmentation helps in achieving an overall relative reduction of \(50.2\%\) in equal error rate.

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Authors and Affiliations

  1. National Institute of Technology Patna, Patna, 800005, Bihar, India

    Shahid Aziz & Syed Shahnawazuddin

  2. Chandigarh University, Mohali, Punjab, India

    Shivesh Pushp

Authors
  1. Shahid Aziz
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  2. Shivesh Pushp
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  3. Syed Shahnawazuddin
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Corresponding author

Correspondence to Shahid Aziz .

Editor information

Editors and Affiliations

  1. St. Petersburg Federal Research Center of the Russian Academy of Sciences, St. Petersburg, Russia

    Alexey Karpov

  2. Koneru Lakshmaiah Education Foundation, Vaddeswaram, India

    K. Samudravijaya

  3. Indian Institute of Information Technology Dharwad, Dharwad, India

    K. T. Deepak

  4. Indian Institute of Technology Dharwad, Dharwad, India

    Rajesh M. Hegde

  5. KIIT Group of Colleges, Gurugram, India

    Shyam S. Agrawal

  6. Indian Institute of Technology Dharwad, Dharwad, India

    S. R. Mahadeva Prasanna

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Aziz, S., Pushp, S., Shahnawazuddin, S. (2023). Studying the Effectiveness of Data Augmentation and Frequency-Domain Linear Prediction Coefficients in Children’s Speaker Verification Under Low-Resource Conditions. In: Karpov, A., Samudravijaya, K., Deepak, K.T., Hegde, R.M., Agrawal, S.S., Prasanna, S.R.M. (eds) Speech and Computer. SPECOM 2023. Lecture Notes in Computer Science(), vol 14339. Springer, Cham. https://doi.org/10.1007/978-3-031-48312-7_32

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  • DOI: https://doi.org/10.1007/978-3-031-48312-7_32

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48311-0

  • Online ISBN: 978-3-031-48312-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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