User-Customized Password Speaker Verification based on HMM/ANN and GMM Models
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The EMIME European project is conducting research in the development of technologies for mobile, personalised speech-tospeech translation systems. The hidden Markov model is being used as the underlying technology in both automatic speech recognition (ASR) ...
In this paper, we investigate the significance of contextual information in a phoneme recognition system using the hidden Markov model - artificial neural network paradigm. Contextual information is probed at the feature level as well as at the output of t ...
In this paper, we investigate the significance of contextual information in a phoneme recognition system using the hidden Markov model - artificial neural network paradigm. Contextual information is probed at the feature level as well as at the output of t ...
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This paper presents a bi-modal (face and speech) authentication demonstration system that simulates the login of a user using its face and its voice. This demonstration is called BioLogin. It runs both on Linux and Windows and the Windows version is freely ...
This paper discusses and optimizes an HMM/GMM based User-Customized Password Speaker Verification (UCP-SV) system. Unlike text-dependent speaker verification, in UCP-SV systems, customers can choose their own passwords with no lexical constraints. The pass ...
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 ...
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The goal of the thesis is to investigate different approaches that combine and integrate Automatic Speech Recognition (ASR) and Speaker Recognition (SR) systems, with applications to (1) User-Customized Password Speaker Verification (UCP-SV) systems, and, ...
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