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In this paper we propose an approach for the problem of single channel source separation of speech and music signals. Our approach is based on representing each source's power spectral density using dictionaries and nonlinearly projecting the mixture signal spectrum onto the combined span of the dictionary entries. We encourage sparsity and continuity of the dictionary coefficients using penalty terms...
In this paper, we present a Turkish speech recognition system we have developed. We will be giving information about the building of our system and tests we conducted on it. SUVoice voice database, along with METU 1.0, was used in the training of our acoustic models. We performed limited vocabulary and large vocabulary recognition tests. We have shown the performance of modernhidden Markov model based...
It is well known that human perception of speech relies both on audio and visual information. However, the physiology of information fusion process in humans is still indefinite which attracts scientists' attention to information fusion process for audio-visual speech recognition. In this work, a novel tandem hybrid approach is introduced for an efficient audio-visual speech recognition system and...
Language modeling for an inflected language such as Arabic poses new challenges for speech recognition and machine translation due to its rich morphology. Rich morphology results in large increases in out-of-vocabulary (OOV) rate and poor language model parameter estimation in the absence of large quantities of data. In this study, we present a joint morphological-lexical language model (JMLLM) that...
In large vocabulary continuous speech recognition (LVCSR) for agglutinative and inflectional languages, we encounter problems due to theoretically infinite full-word lexicon size. Sub-word lexicon units may be utilized to dramatically reduce the out-of-vocabulary rate in test data. One can develop language models based on sub-word units to perform LVCSR. However, it has not always been beneficial...
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