Detection and recognition of nasal consonants in American English
James Glass, Victor W. Zue · 2005
This paper deals with the recognition of nasal consonants, /m, n, η/, in American English. From an acoustic study conducted earlier, parameters found to be useful in distinguishing nasal murmurs from a set of phonemically defined impostors were used in a recognition experiment. The algorithm assumes that the boundaries of the nasals, and their broad phonetic context, are known. Our results, based on 600 sentences spoken by 60 speakers, show that nasal consonants can be distinguished from the impostors with an accuracy of 83.5%. In parallel, a nasal detection algorithm based on a local decision criterion is being developed, using the outputs of an auditory model. Evaluation of its performance on 600 sentences indicates that the nasals are found 96% of the time, with a 2 to 1 impostor-to-nasal ratio. The final step of merging the detection and recognition components has yet to be completed.