Unified Framework Of Feature Based Adaptation For Statistical Speech Synthesis And Recognition
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We investigate a state-of-the-art Speaker Diarization system regarding its behavior on meetings that are much shorter (from 500 seconds down to 100 seconds) than those typically analyzed in Speaker Diarization benchmarks. First, the problems inherent to th ...
In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...
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) ...
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) ...
We investigate a state-of-the-art Speaker Diarization system regarding its behavior on meetings that are much shorter (from 500 seconds down to 100 seconds) than those typically analyzed in Speaker Diarization benchmarks. First, the problems inherent to th ...
The advent of statistical speech synthesis has enabled the unification of the basic techniques used in speech synthesis and recognition. Adaptation techniques that have been successfully used in recognition systems can now be applied to synthesis systems t ...
Frequency Domain Linear Prediction (FDLP) provides an efficient way to represent temporal envelopes of a signal using auto-regressive models. For the input speech signal, we use FDLP to estimate temporal trajectories of sub-band energy by applying linear p ...
Frequency Domain Linear Prediction (FDLP) provides an efficient way to represent temporal envelopes of a signal using auto-regressive models. For the input speech signal, we use FDLP to estimate temporal trajectories of sub-band energy by applying linear p ...
In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...
In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...