Multi-scale audio indexing for translingual spoken document retrieval

H. Wang*, H. Meng, P. Schone, Berlin Chen, W. K. Lo

*此作品的通信作者

研究成果: 雜誌貢獻會議論文同行評審

10 引文 斯高帕斯(Scopus)

摘要

MEI (Mandarin-English Information) is an English-Chinese crosslingual spoken document retrieval (CL-SDR) system developed during the Johns Hopkins University Summer Workshop 2000. We integrate speech recognition, machine translation, and information retrieval technologies to perform CL-SDR. MEI advocates a multi-scale paradigm, where both Chinese words and subwords (characters and syllables) are used in retrieval. The use of subword units can complement the word unit in handling the problems of Chinese word tokenization ambiguity, Chinese homophone ambiguity, and out-of-vocabulary words in audio indexing. This paper focuses on multi-scale audio indexing in MEI. Experiments are based on the Topic Detection and Tracking Corpora (TDT-2 and TDT-3), where we indexed Voice of America Mandarin news broadcasts by speech recognition on both the word and subword scales. In this paper, we discuss the development of the MEI syllable recognizer, the representations of spoken documents using overlapping subword n-grams and lattice structures. Results show that augmenting words with subwords is beneficial to CL-SDR performance.

原文英語
頁(從 - 到)605-608
頁數4
期刊ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
1
出版狀態已發佈 - 2001 九月 26
事件2001 IEEE Interntional Conference on Acoustics, Speech, and Signal Processing - Salt Lake, UT, 美国
持續時間: 2001 五月 72001 五月 11

ASJC Scopus subject areas

  • 軟體
  • 訊號處理
  • 電氣與電子工程

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