Some phonetic recognition experiments using artificial neural nets

This paper is concerned with the application of artificial neural nets to phonetic recognition. The goal is to investigate how the framework of multilayer perceptrons can be exploited in speech recognition when the are augmented with acoustic-phonetic knowledge. Major issues as the choice of the error metric, the use of contextual information, and determination of the training procedure are investigated within a set of experiments that attempt to recognize the 16 vowels in American English. The results, based on some 10000 vowel tokens excised from 1000 sentences spoken by 200 speakers, indicate that a top-choice accuracy of 54% and 67% can be achieved for the context-independent and -dependent networks, respectively