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Showing 1 to 12 of 12 for “"Speaker adaptation"”.
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Rapid speaker adaptation with speaker clustering
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2002.
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Learning speech embeddings for speaker adaptation and speech understanding
… to propose modeling approaches in order to learn speaker embeddings for speaker adaptation or to learn semantic speech embeddings. The second goal is to introduce training objectives that achieve fairness for the ASR and SLU problems. In the case of speaker adaptation, we introduce an auxiliary …
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Evaluation of speaker adaptation algorithms for public access IVR server
… is concerned with evaluating the suitability of speaker adaptation methods for improving the performance of the modern speech recognition using minimal time
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Speaker model adaptation in automatic speech recognition.
… of automatic speech recognition is to achieve speaker independence. It is generally believed that the main difficulty is the inter-speaker variability in which the acoustic characteristics of different speakers are not the same. There are mainly three approaches to overcome this problem; …
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Adaptation of hybrid deep neural network-hidden Markov model speech recognition system using a sub-space approach
… recognition (ASR) system can be enhanced by adaptation of the ASR for a particular speaker or a group of speakers. In ASR, training and testing data often do not follow the same statistics; they are often mismatched, which leads to a gap in performance. The difference between training and …
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Statistical Recursive Estimation Algorithms for Speaker Adaption
… statistical recursive estimation algorithms for speaker adaptation. In this thesis, a unified framework for recursive maximum likelihood estimation and recursive Bayesian learning is first developed and applied to direct hidden Markov model parameter estimation. Then an online Bayesian learning …
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Computational differences between whispered and non-whispered speech
… evaluated. Our approach ef- fectively performs speaker-adaptation for whispered speech acoustic models without needing whispered speech from the target speaker. Results show im- provement over the standard speaker-independent models. Our work opens up additional avenues for research, which are …
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Automatic Speech Recognition Using Deep Neural Networks: New Possibilities
… frequency variations that commonly happen due to speaker and pronunciation differences in speech signals. Moreover, a new CNN structure called limited weight sharing is proposed to better suit special spectral characteristics of speech signals. Our experimental results have shown that the use of a …
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Joint Training Methods for Tandem and Hybrid Speech Recognition Systems using Deep Neural Networks
… parameterised functions can also be applied to speaker adaptation tasks. At the ASR system level, DNN acoustic model and corresponding speaker dependent (SD) input feature transforms are jointly learned through minimum phone error (MPE) training as an example of hybrid system joint training, …
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Using articulatory adjustment to compensate for hypernasality - a modeling study based on measures of electromagnetic articulography (EMA)
… behaviors developed spontaneously by speakers with VPI on individual bases. This study constructed a speaker-adaptive articulatory model on the basis of the framework of Childers’s vocal tract model to simulate articulatory adjustments aiming at compensating for the acoustic outcome …