On MLP-based Posterior Features for Template-based ASR
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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 ...
A speaker diarization system based on an information theoretic framework is described. The problem is formulated according to the {\em Information Bottleneck} (IB) principle. Unlike other approaches where the distance between speaker segments is arbitraril ...
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 ...
This paper investigates the combination of two streams of acoustic features. Extending our previous work on small vocabulary task, we show that combination based on Dempster-Shafer rule outperforms several classical rules like sum, product and inverse entr ...
This paper investigates the combination of two streams of acoustic features. Extending our previous work on small vocabulary task, we show that combination based on Dempster-Shafer rule outperforms several classical rules like sum, product and inverse entr ...
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Multi-stream based automatic speech recognition (ASR) systems outperform their single stream counterparts, specially in case of noisy speech. The main issues in multi-stream systems are: a) Find the feature streams carrying complementary information, and b ...
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