Automatic indexing of multimedia content by integration of audio, spoken language, and visual information

Katsutoshi Ohtsuki; Katsuji Bessho; Yoshihiro Matsuo; Shoichi Matsunaga; Yoshihiko Hayashi

doi:10.1109/ASRU.2003.1318508

Automatic indexing of multimedia content by integration of audio, spoken language, and visual information

Katsutoshi Ohtsuki, Katsuji Bessho, Yoshihiro Matsuo, Shoichi Matsunaga, Yoshihiko Hayashi

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

7 Citations (Scopus)

Abstract

This paper describes an automatic multimedia content indexing system that includes acoustic segmentation, automatic speech recognition, topic segmentation, and video indexing features. The system is intended for indexing of multimedia news programs. Speech segments extracted from news content are delivered to the speech recognition module. The speech recognition result is segmented into topics using a segmentation algorithm based on word conceptual vectors. The indexing results derived from audio and speech information are integrated with video indexing results to extract the story structure. Experimental results show that topic segmentation using word conceptual vectors is superior to the conventional method using local word co-occurrence frequencies, and that the integrated segmentation provides better news story structures than would be possible with any single type of information.

Original language	English
Title of host publication	2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	601-606
Number of pages	6
ISBN (Electronic)	0780379802, 9780780379800
DOIs	https://doi.org/10.1109/ASRU.2003.1318508
Publication status	Published - 2003
Externally published	Yes
Event	IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003 - St. Thomas, United States Duration: 2003 Nov 30 → 2003 Dec 4

Publication series

Name	2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003

Other

Other	IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003
Country/Territory	United States
City	St. Thomas
Period	03/11/30 → 03/12/4

ASJC Scopus subject areas

Signal Processing
Computer Vision and Pattern Recognition
Computer Science Applications

Access to Document

10.1109/ASRU.2003.1318508

Cite this

Ohtsuki, K., Bessho, K., Matsuo, Y., Matsunaga, S., & Hayashi, Y. (2003). Automatic indexing of multimedia content by integration of audio, spoken language, and visual information. In 2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003 (pp. 601-606). [1318508] (2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ASRU.2003.1318508

Automatic indexing of multimedia content by integration of audio, spoken language, and visual information. / Ohtsuki, Katsutoshi; Bessho, Katsuji; Matsuo, Yoshihiro et al.

2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003. Institute of Electrical and Electronics Engineers Inc., 2003. p. 601-606 1318508 (2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Ohtsuki, K, Bessho, K, Matsuo, Y, Matsunaga, S & Hayashi, Y 2003, Automatic indexing of multimedia content by integration of audio, spoken language, and visual information. in 2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003., 1318508, 2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003, Institute of Electrical and Electronics Engineers Inc., pp. 601-606, IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003, St. Thomas, United States, 03/11/30. https://doi.org/10.1109/ASRU.2003.1318508

Ohtsuki K, Bessho K, Matsuo Y, Matsunaga S, Hayashi Y. Automatic indexing of multimedia content by integration of audio, spoken language, and visual information. In 2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003. Institute of Electrical and Electronics Engineers Inc. 2003. p. 601-606. 1318508. (2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003). doi: 10.1109/ASRU.2003.1318508

Ohtsuki, Katsutoshi ; Bessho, Katsuji ; Matsuo, Yoshihiro et al. / Automatic indexing of multimedia content by integration of audio, spoken language, and visual information. 2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003. Institute of Electrical and Electronics Engineers Inc., 2003. pp. 601-606 (2003 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2003).

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abstract = "This paper describes an automatic multimedia content indexing system that includes acoustic segmentation, automatic speech recognition, topic segmentation, and video indexing features. The system is intended for indexing of multimedia news programs. Speech segments extracted from news content are delivered to the speech recognition module. The speech recognition result is segmented into topics using a segmentation algorithm based on word conceptual vectors. The indexing results derived from audio and speech information are integrated with video indexing results to extract the story structure. Experimental results show that topic segmentation using word conceptual vectors is superior to the conventional method using local word co-occurrence frequencies, and that the integrated segmentation provides better news story structures than would be possible with any single type of information.",

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AB - This paper describes an automatic multimedia content indexing system that includes acoustic segmentation, automatic speech recognition, topic segmentation, and video indexing features. The system is intended for indexing of multimedia news programs. Speech segments extracted from news content are delivered to the speech recognition module. The speech recognition result is segmented into topics using a segmentation algorithm based on word conceptual vectors. The indexing results derived from audio and speech information are integrated with video indexing results to extract the story structure. Experimental results show that topic segmentation using word conceptual vectors is superior to the conventional method using local word co-occurrence frequencies, and that the integrated segmentation provides better news story structures than would be possible with any single type of information.

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Automatic indexing of multimedia content by integration of audio, spoken language, and visual information

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