Unsupervised speaker change detection for mobile device recorded speech

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

5 Citations (Scopus)

Abstract

In this paper we propose an unsupervised speaker change detection (SCD) system developed for mobile device applications. We use Bayesian information criterion (BIC) to find initial speaker changes, which are then verified or discarded in the second phase by utilizing modified BIC and silence detector information. Silence information usage after initial BIC in decision making is useful to separate real changes from noise peaks. Enhanced peak detector adjusts BIC penalty parameter automatically, which improve the robustness and feasibility. Improved BIC based false alarm compensation (FAC) merges effectively consecutive segments belonging to same speaker. Our experiments have shown the robustness of the algorithm and it produces very satisfactory results for difficult mobile phone recorded speech data.
Original languageEnglish
Title of host publicationIEEE International Conference on Acoustics, Speech, and Signal Processing. Honolulu, HI, USA, 15-20 April 2007. IEEE Cat. No. 07CH378
PublisherIEEE Institute of Electrical and Electronic Engineers
ISBN (Electronic)1-4244-0728-1
ISBN (Print)1-4244-0727-3
DOIs
Publication statusPublished - 2007
MoE publication typeA4 Article in a conference publication
EventIEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07 - Honolulu, United States
Duration: 15 Apr 200720 Apr 2007

Conference

ConferenceIEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07
Abbreviated titleICASSP '07
CountryUnited States
CityHonolulu
Period15/04/0720/04/07

Fingerprint

Mobile devices
Detectors
Mobile phones
Decision making
Experiments
Compensation and Redress

Keywords

  • Metadata
  • Mobile audio segmentation
  • Multimedia database
  • Speaker change detection
  • Speaker segmentation

Cite this

Vuorinen, O., Peltola, J., & Mäkelä, S-M. (2007). Unsupervised speaker change detection for mobile device recorded speech. In IEEE International Conference on Acoustics, Speech, and Signal Processing. Honolulu, HI, USA, 15-20 April 2007. IEEE Cat. No. 07CH378 IEEE Institute of Electrical and Electronic Engineers . https://doi.org/10.1109/ICASSP.2007.366346
Vuorinen, Olli ; Peltola, Johannes ; Mäkelä, Satu-Marja. / Unsupervised speaker change detection for mobile device recorded speech. IEEE International Conference on Acoustics, Speech, and Signal Processing. Honolulu, HI, USA, 15-20 April 2007. IEEE Cat. No. 07CH378. IEEE Institute of Electrical and Electronic Engineers , 2007.
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Vuorinen, O, Peltola, J & Mäkelä, S-M 2007, Unsupervised speaker change detection for mobile device recorded speech. in IEEE International Conference on Acoustics, Speech, and Signal Processing. Honolulu, HI, USA, 15-20 April 2007. IEEE Cat. No. 07CH378. IEEE Institute of Electrical and Electronic Engineers , IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '07, Honolulu, United States, 15/04/07. https://doi.org/10.1109/ICASSP.2007.366346

Unsupervised speaker change detection for mobile device recorded speech. / Vuorinen, Olli; Peltola, Johannes; Mäkelä, Satu-Marja.

IEEE International Conference on Acoustics, Speech, and Signal Processing. Honolulu, HI, USA, 15-20 April 2007. IEEE Cat. No. 07CH378. IEEE Institute of Electrical and Electronic Engineers , 2007.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingsScientificpeer-review

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N2 - In this paper we propose an unsupervised speaker change detection (SCD) system developed for mobile device applications. We use Bayesian information criterion (BIC) to find initial speaker changes, which are then verified or discarded in the second phase by utilizing modified BIC and silence detector information. Silence information usage after initial BIC in decision making is useful to separate real changes from noise peaks. Enhanced peak detector adjusts BIC penalty parameter automatically, which improve the robustness and feasibility. Improved BIC based false alarm compensation (FAC) merges effectively consecutive segments belonging to same speaker. Our experiments have shown the robustness of the algorithm and it produces very satisfactory results for difficult mobile phone recorded speech data.

AB - In this paper we propose an unsupervised speaker change detection (SCD) system developed for mobile device applications. We use Bayesian information criterion (BIC) to find initial speaker changes, which are then verified or discarded in the second phase by utilizing modified BIC and silence detector information. Silence information usage after initial BIC in decision making is useful to separate real changes from noise peaks. Enhanced peak detector adjusts BIC penalty parameter automatically, which improve the robustness and feasibility. Improved BIC based false alarm compensation (FAC) merges effectively consecutive segments belonging to same speaker. Our experiments have shown the robustness of the algorithm and it produces very satisfactory results for difficult mobile phone recorded speech data.

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KW - Mobile audio segmentation

KW - Multimedia database

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KW - Speaker segmentation

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Vuorinen O, Peltola J, Mäkelä S-M. Unsupervised speaker change detection for mobile device recorded speech. In IEEE International Conference on Acoustics, Speech, and Signal Processing. Honolulu, HI, USA, 15-20 April 2007. IEEE Cat. No. 07CH378. IEEE Institute of Electrical and Electronic Engineers . 2007 https://doi.org/10.1109/ICASSP.2007.366346