Comparison of continuous speech recognition systems with unknown-word processing for speech disfluencies

✍ Scribed by Atsuhiko Kai; Seiichi Nakagawa

• Publisher: John Wiley and Sons
• Year: 1998
• Tongue: English
• Weight: 594 KB
• Volume: 29
• Category: Article
• ISSN: 0882-1666
• DOI: 10.1002/(sici)1520-684x(199808)29:9<43::aid-scj5>3.0.co;2-j

✦ Synopsis

This paper describes speech recognition systems for dealing with spontaneous speech, in which an unknownword processing method based on subword sequence decoding is employed. We propose an efficient algorithm for unknown-word processing that employs an independent process of subword sequence decoding while an utterance is verified and searched with an appropriate linguistic constraint. The algorithm is applied both to one pass-based and spotting-based search algorithms after small modification. We compared speech understanding systems whose recognition strategies differ in terms of the search strategies and with the way of handling unknown words and interjections. We observed that the effectiveness of the unknown-word processing technique depends on the accuracy of the acoustic model and that a one pass-based search algorithm with unknown-word processing attains the best performance for phrase/sentence accuracy and computational efficiency, although the sentence understanding rate for the evaluated task is comparable to or slightly less than the best among other methods. The experimental results showed that when the unknown-word processing technique was employed to deal with extraneous speech, a sentence understanding rate of 80% was attained for a task with a test set perplexity of 40.