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Multilingual Articulatory Features For Speech Recognition, Brian M. Ore

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Articulatory features describe the way in which the speech organs are used when producing speech sounds. Research has shown that incorporating this information into speech recognizers can lead to an improvement in system performance. The majority of previous work, however, has been limited to detecting articulatory features in a single language. In this thesis, Gaussian Mixture Models (GMMs) and Multi-Layer Perceptrons (MLPs) were used to detect articulatory features in English, German, Spanish, and Japanese. The outputs of the detectors were used to form the feature set for a Hidden Markov Model (HMM)-based phoneme recognizer. The best overall detection and recognition …