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Stress has effect on speech characteristics and can influence the quality of speech. In this paper, we study the effect of Sleep-Deprivation (SD) on speech characteristics and classify Normal Speech (NS) and Sleep Deprived Speech (SDS). One of the indicators of sleep deprivation is 'flattened voice'. We examine pitch and harmonic locations to analyse(More)
Natural pitch fluctuations are essential to human singing. To effectively synthesize singing voice, the generation of these pitch fluctuations is necessary. Previous synthesis methods classify and reproduce them individually. These fluctuations, however, are found to be dependent and vary under different contexts. This paper proposes a generalized framework(More)
This paper describes our recent efforts in exploring effective discriminative features for speaker recognition. Recent researches have indicated that the appropriate fusion of features is critical to improve the performance of speaker recognition system. In this paper we describe our approaches for the NIST 2006 Speaker Recognition Evaluation. Our system(More)
The paper presents a unit selection-based speech synthesis approach for mandarin Chinese. Unit selection-based approach generates speech by selecting proper units from a speech corpus and connecting them together. In this approach, a set of features are defined to describe the speech units in the corpus and the expected units in the synthesized utterance.(More)
We provide the raw data for protein and peptide identification and quantization of superior and inferior spikelets in hybrid rice during grain filling. The mass spectrometry proteomics data have been deposited to the Proteome Xchange Consortium via the PRIDE partner repository with the dataset identifier PXD001046. Our data presented here is also related to(More)
Emotional facial expression transfer involves sequence-to-sequence mappings from an neutral facial expression to another emotional facial expression, which is a well-known problem in computer graphics. In the graphics community, current considered methods are typically linear (e.g., methods based on blendshape mapping) and the dynamical aspects of the(More)
In this paper, an onset detection method based on Simple Partial Least Squares (SIMPLS) is proposed and a system of fusing SIMPLS and SuperFlux is introduced. SIMPLS is an efficient approach to partial least squares regression which has been applied to classification tasks. To detect onsets in an audio file, the file is sampled discretely into frames and(More)