Yasuo Horiuchi

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Denoising autoencoder is applied to reverberant speech recognition as a noise robust front-end to reconstruct clean speech spectrum from noisy input. In order to capture context effects of speech sounds, a window of multiple short-windowed spectral frames are concatenated to form a single input vector. Additionally, a combination of short and long-term(More)
In sign language, hand positions and movements represent meaning of words. Hence, we have been developing sign language recognition methods using both of hand positions and movements. However, in the previous studies, each feature has same weight to calculate the probability for the recognition. In this study, we propose a sign language recognition method(More)
Collaborative filtering (CF) is one of the most popular recommender system technologies. It tries to identify users that have relevant interests and preferences by calculating similarities among user profiles. The idea behind this method is that, it may be of benefit to one's search for information to consult the preferences of other users who share the(More)
In this study, we introduce a method of estimating the syntactic tree structure of Japanese speech on the basis of the F0 contour and the time duration. We introduce a method of estimating the syntactic structure including the following phrase by using the local prosodic features of the first and final part of the leading phrase. This method involves(More)
In text-independent (TI) speaker identification, the variation of phonetic information strongly affects the performance of speaker identification. If this phonetic information in his/her speech data can be suppressed, a robust TI speaker identification system will be realized by using speech features having less phonetic information. In this paper, we(More)