Recent advances in the multi-stream HMM/ANN hybrid approach to noise robust ASR
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We propose a technique for generating alternative models for keywords in a hybrid hidden Markov model - artificial neural network (HMM-ANN) keyword spotting paradigm. Given a base pronunciation for a keyword from the lookup dictionary, our algorithm genera ...
We address the problem of recognizing sequences of human interaction patterns in meetings, with the goal of structuring them in semantic terms. The investigated patterns, are inherently group-based (defined by the individual activities of meeting participa ...
This paper proposes a novel and simple local neural classifier for the recognition of mental tasks from on-line spontaneous EEG signals. The proposed neural classifier recognizes three mental tasks from on-line spontaneousEEGsignals. Correct recognition is ...
Institute of Electrical and Electronics Engineers2002
We address the problem of recognizing sequences of human interaction patterns in meetings, with the goal of structuring them in semantic terms. The investigated patterns, are inherently group-based (defined by the individual activities of meeting participa ...
Traditional speech recognition systems use Gaussian mixture models to obtain the likelihoods of individual phonemes, which are then used as state emission probabilities in hidden Markov models representing the words. In hybrid systems, the Gaussian mixture ...
In this paper, we present a new approach towards user-custom-ized password speaker verification combining the advantages of hybrid HMM/ANN systems, using Artificial Neural Networks (ANN) to estimate emission probabilities of Hidden Markov Models, and Gaus ...
In this paper, we present a new approach towards user-custom-ized password speaker verification combining the advantages of hybrid HMM/ANN systems, using Artificial Neural Networks (ANN) to estimate emission probabilities of Hidden Markov Models, and Gaus ...
