From missing data to maybe useful data: soft data modelling for noise robust ASR
Publications associées (34)
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Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models (HMMs), with a p ...
We address issues for improving hands-free speech recognition performance in the presence of multiple simultaneous speakers using multiple distant microphones. In this paper, a log spectral mapping is proposed to estimate the log mel-filterbank outputs of ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models~(HMMs), with a p ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models (HMMs), with a p ...
The work described in this thesis takes place in the context of capturing real-life audio for the analysis of spontaneous social interactions. Towards this goal, we wish to capture conversational and ambient sounds using portable audio recorders. Analysis ...
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 ...
Many state-of-the-art segmentation algorithms rely on Markov or Conditional Random Field models designed to enforce spatial and global consistency constraints. This is often accomplished by introducing additional latent variables to the model, which can gr ...
In this work, we propose different strategies for efficiently integrating an automated speech recognition module in the framework of a dialogue-based vocal system. The aim is the study of different ways leading to the improvement of the quality and robustn ...
Using phone posterior probabilities has been increasingly explored for improving automatic speech recognition (ASR) systems. In this paper, we propose two approaches for hierarchically enhancing these phone posteriors, by integrating long acoustic context, ...