Phoneme segmentation expert system using spectrogram reading knowledge

✍ Scribed by Kaichiro Hatazaki; Yasuhiro Komori; Takeshi Kawabata; Kiyohiro Shikano

• Publisher: John Wiley and Sons
• Year: 1990
• Tongue: English
• Weight: 908 KB
• Volume: 21
• Category: Article
• ISSN: 0882-1666
• DOI: 10.1002/scj.4690211210

✦ Synopsis

Abstract

A human expert is able to determine phoneme boundaries through spectrogram reading with high accuracy using one's knowledge and strategy. The authors developed a phoneme segmentation expert system which simulates a human expert spectrogram reading process using knowledge and strategy. This expert system detects phonemes from a continuous speech spectrogram and determines phoneme boundaries with their coarsely classified phoneme according to human expert knowledge and strategy which is described as rules. An assumption‐based inference with certainty factors and top‐down acoustic feature extraction under phoneme context hypotheses are incorporated into the expert system to simulate the phoneme contextual fuzzy knowledge and strategy used by a human expert. This framework makes it possible to deal with phoneme variations caused by coarticulation, and to extract accurate acoustic features on a spectrogram for phoneme segmentation. Japanese consonant segmentation knowledge currently is incorporated into the system which detected 90.8 percent of the phonemes correctly. In particular, the average alignment error of phoneme boundaries detected by the system was 5.8 ms, which is as accurate as those detected by a human expert.