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RNN-based prosodic modeling for mandarin speech and its application to speech-to-text conversion
2002
Speech Communication
In this paper, a recurrent neural network (RNN) based prosodic modeling method for Mandarin speech-to-text conversion is proposed. The prosodic modeling is performed in the post-processing stage of acoustic decoding and aims at detecting word-boundary cues to assist in linguistic decoding. It employs a simple three-layer RNN to learn the relationship between input prosodic features, extracted from the input utterance with syllable boundaries pre-determined by the preceding acoustic decoder, and
doi:10.1016/s0167-6393(01)00006-1
fatcat:ig7ehvd5xfhs5oecglcn25qq2q