Vowel place detection for a knowledge‐based speech recognition system

This work aims to detect vowel place as part of a knowledge‐based speech recognition system. Vowel place was classified into 6 groups based on tongue advancement [Front/Back] and height [High/Mid/Low]. Experiments were performed using 300 /hVd/ utterance data from Hillenbrand [J. Acoust. Soc. Am. 97, 3099‐3111] and 6600 TIMIT vowels. Features used include fundamental frequency (F0) and formant value (F1̃F3), where formant measurements were classified into separate groups using F0 measurements. The nearest class was found using a simple Mahalanobis distance measure, and yielded a 91.5% classification rate for the /hVd/ data. The results for the TIMIT data were 64.4%, and error analysis with regard to adjacent segment manner and place was carried out to observe the effects of coarticulation, which was not observed in the /hVd/ data.