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This paper investigates a new approach for detecting phoneme level mispronunciations from utterances obtained from impaired children with neuromuscular disorders. This new pronunciation verification (PV) approach is obtained from the subspace based Gaussian mixture model (SGMM) based pronunciation model, where a set of state level projection vectors is applied for representing phonetic variability...
This paper investigates the impact of subspace based techniques for acoustic modeling in automatic speech recognition (ASR). There are many well known approaches to subspace based speaker adaptation which represent sources of variability as a projection within a low dimensional subspace. A new approach to acoustic modeling in ASR, referred to as the subspace based Gaussian mixture model (SGMM), represents...
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