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2020 Fiscal Year Annual Research Report

Study on Audio Information Hiding Based on Human Auditory Perception with Phase Modulation

Research Project

Project/Area Number 20J20580
Research InstitutionJapan Advanced Institute of Science and Technology

Principal Investigator

MAWALIM CANDY OLIVIA  北陸先端科学技術大学院大学, 先端科学技術研究科, 特別研究員(DC1)

Project Period (FY) 2020-04-24 – 2023-03-31
Keywordsinformation hiding / speech coding / voice privacy / speaker anonymization
Outline of Annual Research Achievements

In the first year, the investigation on audio information hiding (AIH) for secure speech communication systems was conducted. AIH often lacks robustness in dealing with speech codecs, which are efficiently used in a speech communication system. Accordingly, the experiment on a code-excited linear prediction (CELP) codec was carried out to analyze the robust features for AIH. The principal investigator found out that the line spectral frequencies are robust features against the CELP codec. The results of this experiment were reported in the APSIPA proceeding 2020. Besides, the investigation of a method to secure voice privacy based on the information hiding concept was also conducted. The results were reported in the Interspeech proceeding 2020 and a journal (submitted).

Current Status of Research Progress
Current Status of Research Progress

2: Research has progressed on the whole more than it was originally planned.

Reason

The progress of this study is going well as planned. The CELP codec was analyzed thoroughly at this stage, and some robust features were investigated as information hiding mediums. The principal investigator presented the experiments on modification of LSFs (one of the robust features) in a paper at APSIPA 2020 conference. The information hiding concept was also considered to hide speaker individuality for securing voice privacy. The technique for hiding speaker individuality is based on the VoicePrivacy Challenge 2020 (VP2020), namely the speaker anonymization approach. The principal investigator participated in the VP2020, and the results were reported in the Interspeech 2020 conference. The extended results were also submitted in the special issue of voice privacy as a journal paper.

Strategy for Future Research Activity

Despite the promising results, there were still some remaining problems in AIH using LSFs modification. The main reason is due to LSB that fragile for detection. As one of future works, the phase modulation on LSFs will be investigated to deal with this problem. For speaker anonymization, the trade-off issue between speech intelligibility and speaker verifiability in the speaker anonymization method is existing. The consideration of the current proposed method framework will be improved by modifying the model and parameters. In addition to this trade-off issue, the evaluation of speaker anonymization is still somehow inadequate. As future work, the more appropriate subjective and objective evaluation will be carried out by considering the phenomena in human auditory perception.

  • Research Products

    (5 results)

All 2021 2020

All Journal Article (2 results) (of which Int'l Joint Research: 2 results,  Peer Reviewed: 2 results,  Open Access: 1 results) Presentation (3 results) (of which Int'l Joint Research: 2 results)

  • [Journal Article] X-Vector Singular Value Modification and Statistical-Based Decomposition with Ensemble Regression Modeling for Speaker Anonymization System2020

    • Author(s)
      Mawalim Candy Olivia、Galajit Kasorn、Karnjana Jessada、Unoki Masashi
    • Journal Title

      Proc. Interspeech 2020

      Volume: - Pages: 1703,1707

    • DOI

      10.21437/Interspeech.2020-1887

    • Peer Reviewed / Open Access / Int'l Joint Research
  • [Journal Article] Speech Information Hiding by Modification of LSF Quantization Index in CELP Codec2020

    • Author(s)
      Candy Olivia Mawalim, Shengbei Wang, Masashi Unoki
    • Journal Title

      Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, {APSIPA} 2020, Auckland, New Zealand, December 7-10, 2020

      Volume: - Pages: 1321,1330

    • Peer Reviewed / Int'l Joint Research
  • [Presentation] X-vector anonymization using regression modeling with statistical and singular value decomposition2021

    • Author(s)
      Candy Olivia Mawalim, Kasorn Galajit, Jessada Karnjana, Masashi Unoki
    • Organizer
      電子情報通信学会EMM研究会
  • [Presentation] X-Vector Singular Value Modification and Statistical-Based Decomposition with Ensemble Regression Modeling for Speaker Anonymization System2020

    • Author(s)
      Candy Olivia Mawalim, Kasorn Galajit, Jessada Karnjana, Masashi Unoki
    • Organizer
      Interspeech2020
    • Int'l Joint Research
  • [Presentation] Speech Information Hiding by Modification of LSF Quantization Index in CELP Codec2020

    • Author(s)
      Candy Olivia Mawalim, Shengbei Wang, Masashi Unoki
    • Organizer
      APSIPA2020
    • Int'l Joint Research

URL: 

Published: 2021-12-27  

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