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This paper describes recent improvements to the Cambridge Arabic Large Vocabulary Continuous Speech Recognition (LVSCR) Speech-to-Text (STT) system. It is shown that Multi-Layer Perceptron (MLP) features trained on phonetic targets can improve the performance of both phonemic and graphemic systems. Also, a morphological decomposition scheme is extended from the graphemic domain to the phonetic domain,...
Features derived from multilayer perceptrons (MLPs) are becoming increasingly popular for speech recognition. This paper describes various schemes for applying these features to state-of-the-art Arabic speech recognition: the use of MLP-features for short-vowel modelling in graphemic systems; rapid discriminative model training by standard PLP feature lattice reuse; and MLP feature adaptation using...
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