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This paper presents a multi-channel/multi-speaker 3D audio-visual corpus for Mandarin continuous speech recognition and other fields, such as speech visualization and speech synthesis. This corpus consists of 24 speakers with about 18k utterances, about 20 hours in total. For each utterance, the audio streams were recorded by two professional microphones in near-field and far-field respectively, while...
Recently, convolutional neural networks (CNNs) have been applied successfully to acoustic modelling in speech recognition. As the bottleneck features from CNNs contain inherently discriminative and rich context information, the standard approach is to augment the conventional acoustic features with the CNN bottleneck features in a tandem framework. To better capture the highly complex relationship...
An important task for speech recognition systems is to handle the mismatch against a target environment introduced by acoustic factors such as variable ambient noise. To address this issue, it is possible to explicitly approximate the continuous trajectory of optimal, well matched model parameters against the varying noise using, for example, using generalized variable parameter HMMs (GVP-HMM). In...
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