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Titlebook: Computational Models of Speech Pattern Processing; Keith Ponting Book 1999 Springer-Verlag Berlin Heidelberg 1999 Dialogue systems.Human s

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Supercomputing: Key Issues and Challengesistic hypotheses. So far, the most useful prosodic information is provided by clause boundaries. These are detected with a recognition rate of 94%. For the parsing of word hypotheses graphs, the use of clause boundary probabilities yields a speed-up of 92% and a 96% reduction of alternative readings.
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Acoustic Modelling for Large Vocabulary Continuous Speech Recognition,tation allows a set of HMM parameter transforms to be robustly estimated using small amounts of adaptation data. Secondly, MMI training based on lattices can be used to increase the inherent discrimination of the HMMs.
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Science, Simulation and Supercomputersn assessed on a frame by frame phonetic identification on the TIMIT database. Thereafter, a method to integrate the K-NN pdf estimator in a HMM-based system is proposed and tested on an acoustic-phonetic decoding task.
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