Speech recognition based on acoustically derived segment units

Toshiaki Fukada*, Michiel Bacchiani, Kuldip K. Paliwal, Yoshinori Sagisaka

*この研究の対応する著者

研究成果: Paper査読

8 被引用数 (Scopus)

抄録

This paper describes a new method of word model generation based on acoustically derived segment units (henceforth ASUs). An ASU-based approach has the advantages of growing out of human pre-determined phonemes and of consistently generating acoustic units by using the maximum likelihood (ML) criterion. The former advantage is effective when it is difficult to map acoustics to a phone such as with highly co-articulated spontaneous speech. In order to implement an ASU-based modeling approach in a speech recognition system, we must first solve two points: (1) How do we design an inventory of acoustically-derived segmental units and (2) How do we model the pronunciations of lexical entries in terms of the ASUs. As for the second question, we propose an ASU-based word model generation method by composing the ASU statistics, that is, their means, variances and durations. The effectiveness of the proposed method is shown through spontaneous word recognition experiments.

本文言語English
ページ1077-1080
ページ数4
出版ステータスPublished - 1996 12 1
外部発表はい
イベントProceedings of the 1996 International Conference on Spoken Language Processing, ICSLP. Part 1 (of 4) - Philadelphia, PA, USA
継続期間: 1996 10 31996 10 6

Other

OtherProceedings of the 1996 International Conference on Spoken Language Processing, ICSLP. Part 1 (of 4)
CityPhiladelphia, PA, USA
Period96/10/396/10/6

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)

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