Skip to main content
SpringerLink
Log in

Speaker Diarization in Vietnamese Voice

  • Conference paper
  • First Online:
Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications (FDSE 2021)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1500))

Included in the following conference series:

  • 1147 Accesses

Abstract

Speaker diarization is the process of partitioning an input audio stream into homogeneous segments according to different speakers. It is an important process to support speaker recognition systems and identify a speaker in broadcasts, meeting recordings, and voice mail. Especially it is a fundamental step of automatic checklist reading evaluation system in operating rooms. In this study, we introduce an approach for speaker diarization in Vietnamese voices. The proposed method consists of vectorizing voice based on x-vector and then clustering by mean-shift, k-means, and agglomerative hierarchical techniques to identify speakers in audio. This method attained the accuracy of 89.29% on the 2-speaker mock dialogue generated from the testing set of the VIVOS Corpus dataset.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 79.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 99.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Anguera, X., Bozonnet, S., Evans, N., Fredouille, C., Friedland, G., Vinyals, O.: Speaker diarization: a review of recent research. IEEE Trans. Audio Speech Lang. Process. 20(2), 356–370 (2012)

    Article  Google Scholar 

  2. Gish, H., Siu, M.H., Rohlicek, R.: Segregation of speakers for speech recognition and speaker identification. In: Proceedings of IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 873–876 (1991)

    Google Scholar 

  3. Gauvain, J.L., Lamel, L., Adda, G., Jardino: The LIMSI 1997 Hub-4E transcription system. In: Proceedings of DARPA News Transcription and Understanding Workshop, pp. 75–79 (1999)

    Google Scholar 

  4. Wooters, C., Fung, J., Peskin, B., Anguera, X.: Towards robust speaker segmentation: The ICSI-SRI Fall 2004 diarization system. In: Proceedings of Fall 2004 Rich Transcription Workshop, pp. 402–414 (2004)

    Google Scholar 

  5. Rosenberg, A.E., Gorin, A., Liu, Z., Parthasarathy, S.: Unsupervised speaker segmentation of telephone conversations. In: Seventh International Conference on Spoken Language Processing, pp. 565–568 (2002)

    Google Scholar 

  6. Jin, Q., Schultz, T.: Speaker segmentation and clustering in meetings. In: Proceedings of the International Conference on Spoken Language Processing, pp. 597–600 (2004)

    Google Scholar 

  7. Anguera, X., Wooters, C., Hernando, J.: Acoustic beamforming for speaker diarization of meetings. IEEE Trans. Audio Speech Lang. Process. 15(7), 2011–2023 (2007)

    Article  Google Scholar 

  8. Vijayasenan, D., Valente, F., Bourlard, H.: An information theoretic approach to speaker diarization of meeting data. IEEE Trans. Audio Speech Lang. Process. 17(7), 1382–1393 (2009)

    Article  Google Scholar 

  9. Valente, F., Motlicek, P., Vijayasenan, D.: Variational bayesian speaker diarization of meeting recordings. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 4954–4957 (2010)

    Google Scholar 

  10. Kenny, P., Boulianne, G., Ouellet, P., Dumouchel, P.: Joint factor analysis versus eigenchannels in speaker recognition. IEEE Trans. Audio Speech Lang. Process. 15(4), 1435–1447 (2007)

    Article  Google Scholar 

  11. Variani, E., Lei, X., McDermott, E., Moreno, I.L., Gonzalez-Dominguez, J.: Deep neural networks for small footprint text-dependent speaker verification. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 4052–4056 (2014)

    Google Scholar 

  12. Snyder, D., Garcia-Romero, D., Sell, G., Povey, D., Khudanpur, S.: X-vectors: robust DNN embeddings for speaker recognition. In: IEEE International Conference on Acoustics, Speech and Signal Processing, pp. 5329–5333 (2018)

    Google Scholar 

  13. Dehak, N., Kenny, P.J., Dehak, R., Dumouchel, P., Ouellet, P.: Front-end factor analysis for speaker verification. IEEE Trans. Audio Speech Lang. Process. 19(4), 788–798 (2010)

    Article  Google Scholar 

  14. Fujita, Y., Kanda, N., Horiguchi, S., Nagamatsu, K., Watanabe, S.: End-to-end neural speaker diarization with permutation-free objectives. In: Proceedings of the Annual Conference of the International Speech Communication Association, pp. 4300–4304 (2019)

    Google Scholar 

  15. Hien, P.T.T.: Phuong phap i-vector trong nhan dien giong noi. In: Tap chi KHCN Dai hoc thai nguyen (172), 25–29 (2017)

    Google Scholar 

  16. Huy, N.V., Mai, L.C., Thang, V.T.: Applying bottle neck feature for vietnamese speech recognition. J. Comput. Sci. Cybern. 29(4), 379–388 (2013)

    Google Scholar 

  17. Luong, H.T., Vu, H.Q.: A non-expert Kaldi recipe for Vietnamese speech recognition system. In: Proceedings of the Third International Workshop on Worldwide Language Service Infrastructure and Second Workshop on Open Infrastructures and Analysis Frameworks for Human Language Technologies, pp. 51–55 (2016)

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Information Technology, Industrial University of Ho Chi Minh City, Ho Chi Minh City, Vietnam

    Nguyen Duc Nam & Hieu Trung Huynh

Authors
  1. Nguyen Duc Nam
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Hieu Trung Huynh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Hieu Trung Huynh .

Editor information

Editors and Affiliations

  1. HCMC University of Technology (HCMUT), Ho Chi Minh City, Vietnam

    Tran Khanh Dang

  2. Johannes Kepler University of Linz, Linz, Austria

    Josef Küng

  3. Sungkyunkwan University, Suwon, Korea (Republic of)

    Tai M. Chung

  4. Hosei University, Tokyo, Japan

    Makoto Takizawa

Rights and permissions

Reprints and permissions

Copyright information

© 2021 Springer Nature Singapore Pte Ltd.

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Nam, N.D., Huynh, H.T. (2021). Speaker Diarization in Vietnamese Voice. In: Dang, T.K., Küng, J., Chung, T.M., Takizawa, M. (eds) Future Data and Security Engineering. Big Data, Security and Privacy, Smart City and Industry 4.0 Applications. FDSE 2021. Communications in Computer and Information Science, vol 1500. Springer, Singapore. https://doi.org/10.1007/978-981-16-8062-5_31

Download citation

  • DOI: https://doi.org/10.1007/978-981-16-8062-5_31

  • Published:

  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-16-8061-8

  • Online ISBN: 978-981-16-8062-5

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation