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The reverberant speech segregation is a basic problem in speech enhancement and automatic speech recognition. Based on the deep neural networks (DNN), a novel binaural speech segregation method is proposed. The binaural feature is extracted and used as the cue to train a DNN with a ideal parameter mask. The trained DNN is used to distinguish the target speech and noise, and output the estimated parameter...
Speaker recognition in short speech condition is a difficult topic because the length of training and test speech is very short. One of the main disadvantage of the existing methods for speaker recognition is that they need very sufficient data and it's usually impossible in reality applications. In our experiments, the conventional methods with single feature don't make good performance in short...
Based on analyses of characteristic differences between various audio events, a two-level approach is proposed for detecting three non-lexical audio events (filled pause, laugh, and applause) in spontaneous odel-based decision. The experiments give average precision of 87.3%, recall of 93.77%, and F-measure of 90.42%. Compared with the sliding window based approach, average F-measure is improved by...
The human voice not only provides information about the semantics of spoken words, but also contains voice information based on its characteristics. This paper designed feasible identification system for non-semantics voice information by language and gender, which are the two most important in voice signals. The proposed system is speaker-independent and text-independent: it fuses the language and...
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