Issues with uncertainty decoding for noise robust automatic speech recognition
نویسندگان
چکیده
منابع مشابه
Issues with uncertainty decoding for noise robust automatic speech recognition
Interest is growing in a class of robustness algorithms that exploit the notion of uncertainty introduced by environmental noise. The majority of these techniques share the property that the uncertainty of an observation due to noise is propagated to the recogniser, resulting in increased model variances. Using appropriate approximations, efficient implementations may be obtained, with the goal...
متن کاملIssues with uncertainty decoding for noise robust speech recognition
Recently there has been interest in uncertainty decoding for robust speech recognition. Here the uncertainty associated with the observation in noise is propagated to the recogniser. By using appropriate approximations for this uncertainty, it is possible to obtain efficient implementations during decoding. The aim of these schemes is to obtain performance which is close to that of a modelbased...
متن کاملUncertainty Decoding for Noise Robust Automatic Speech Recognition
This report presents uncertainty decoding as a method for robust automatic speech recognition for the Noise Robust Automatic Speech Recognition project funded by Toshiba Research Europe Limited. The effects of noise on speech recognition are reviewed and a general framework for noise robust speech recognition introduced. Common and related noise robustness techniques are described in the contex...
متن کاملUncertainty Decoding for Noise Robust Speech Recognition
Declaration This dissertation is the result of my own work and includes nothing which is the outcome of work done in collaboration. It has not been submitted in whole or in part for a degree at any other university. Some of the work has been published previously in conference proceedings [93, 94, 95] and technical reports [90, 91, 92]. The length of this thesis including appendices, references,...
متن کاملJoint uncertainty decoding for noise robust speech recognition
Background noise can have a significant impact on the performance of speech recognition systems. A range of fast featurespace and model-based schemes have been investigated to increase robustness. Model-based approaches typically achieve lower error rates, but at an increased computational load compared to feature-based approaches. Thismakes their use inmany situations impractical. The uncertai...
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ژورنال
عنوان ژورنال: Speech Communication
سال: 2008
ISSN: 0167-6393
DOI: 10.1016/j.specom.2007.10.004