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Abstract: Pronunciation evaluation systems used by many people in the same place at one time need to evaluate the pronunciation robustly.
abstractEPronunciation evaluation systems used by many people in the same place at one time need to evaluate the pronunciation robustly.
In order to deal with the robust problem, this paper first applies multi-training plus adaptation for acoustic models refinement as in robust speech recognition ...
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Bibliographic details on Robust pronunciation evaluation in adverse environments.
Robust pronunciation evaluation in adverse environments. S. Wei, Q. Gao, G ... Robust pronunciation evaluation in adverse environments. %U http://dblp ...
In this section, a novel approach to detecting and correcting the edit disfluency in spontaneous speech is presented. Hypothesis testing using acoustic features ...
recognition to be achieved in adverse environments. Our study has focused on the SPINE speech in noise corpus developed by. NRL. We developed a baseline ...
The first task is presented to investigate the effectiveness of ICA unsupervised learning for multiple acoustic models based on hidden Markov models (HMMs) ...
Acero et al. Environmental robustness in automatic speech recognition. J.S. Bridle. A noise compensating spectrum distance measure applied to automatic speech ...
Missing: pronunciation | Show results with:pronunciation
In this paper, we propose a noise robust model for auto- matic word-level pronunciation assessment. The network con- sists of a word pronunciation scoring model ...
Missing: adverse | Show results with:adverse