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This paper describes a noise-robust front-end designed within a collaboration of Motorola, France Télécom and Alcatel for the ETSI standardization of the advanced front-end for distributed speech recognition (DSR). The proposed algorithm is based on the cumulative knowledge in the three companies' history in the areas of noise reduction, speech enhancement(More)
In this paper, we introduce a new concept in advancing the noise robustness of speech recognition front-end. The presented method, called SNR-dependent Waveform Processing (SWP), exploits SNR variability within a speech period for enhancing the high SNR period portion and attenuating the low SNR period portion in the waveform time domain. In this way, the(More)
We describe a method of indexing and efficiently searching music melodies based on their continuous dominant fundamental frequency (f0) contours without obtaining note-level transcriptions. Each f0 contour is encoded by a redundant set of wavelet coefficients that represent its shape in level-normalized form at various locations and time scales. This allows(More)
We propose a novel method of efficiently searching very large populations of speakers, tens of thousands or more, using an utterance comparison model proposed in a previous work. The model allows much more efficient comparison of utterances compared to the traditional Gaussian Mixture Model(GMM)-based approach because of its computational simplicity while(More)