Recognition of unaspirated plosives--A statistical approach

In this paper the results of a study of the computer recognition of unaspirated plosives in commonly used polysyllabic words uttered by three different informants are presented. The onglide transitions of the first two formants and their durations have been found to be an effective set of features for the recognition of unaspirated plosives. The rates of transition of these two formants as a feature set have been found to be significantly inferior to the features mentioned earlier. The maximum likelihood method, under the assumption of a normal distribution for the feature set, provides an adequate tool for classification. The assumption of both intergroup and intragroup independence of the features reduces recognition scores. A prior knowledge of target vowels is found necessary for attaining reasonable efficiency. A prior knowledge of voicing manner improves classification efficiency to some extent. The physiological factors responsible for the variation of the recognition score for the various plosives are discussed. For labials and velars the recognition score is very high, nearly 90 percent. An attempt to correlate the dynamics of tongue-body motion with the variations in recognition scores has been made. Back vowels as targets have been found to give improved classification of the preceding consonants. A comparison of the result of machine recognition with those of published results on perception tests has been included. The results are found to be of the same order.