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An investigation on classification of emotional speech cross different language families is proposed in this paper. Datasets on three languages, CDESD in Mandarin, Emo-DB in German, and DES in Danish are analyzed. With 2-D classifications on arousal-appraisal space, better recognition performances are observed in arousal dimension than in appraisal dimension. The classification rates in cross language...
A cross-corpus classification of emotional speech on two datasets, Emo-DB in German and DES in Danish is investigated in this paper. 2-D classifications on arousal-appraisal space leads to significant improvement than in one-step classifications. Emotions are better recognized in arousal dimension than in appraisal dimension. The best classification rate in the cross-corpus test is achieved on male...
An endpoint detection in low signal-to-noise ratio (SNR) environment plays an important role in speech processing. In this paper, we propose an endpoint detection algorithm applying a novel feature parameter, called Spectrogram Boundary Factor (SBF), to improve the endpoint detection performance in noisy environments. In the first step, the time-frequency spectrogram is obtained from the noisy speech...
Speaker recognition plays an important role in speech processing and classification. In this paper, we propose a features extraction method using Perception Auditory Factor to improve the performance of speaker recognition in noisy environment. After the speech enhancement based on auditory perception characteristic and the 2-dimension enhancement for spectrogram, speech distribution is obtained from...
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