Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition

Original eigenphone speaker adaptation method performed well when the amount of adaptation data was suffi-cient.However,it suffered from server overfitting when insufficient amount of adaptation data was provided.A sparse group LASSO(SGL) constraint eigenphone speaker adaptation method was proposed....

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Main Authors: Dan QU, Wen-lin ZHANG
Format: Article
Language:zho
Published: Editorial Department of Journal on Communications 2015-09-01
Series:Tongxin xuebao
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Online Access:http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2015241/
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author Dan QU
Wen-lin ZHANG
author_facet Dan QU
Wen-lin ZHANG
author_sort Dan QU
collection DOAJ
description Original eigenphone speaker adaptation method performed well when the amount of adaptation data was suffi-cient.However,it suffered from server overfitting when insufficient amount of adaptation data was provided.A sparse group LASSO(SGL) constraint eigenphone speaker adaptation method was proposed.Firstly,the principle of eigenphone speaker adaptation was introduced in case of hidden Markov model-Gaussian mixture model (HMM-GMM) based speech recognition system.Then,a sparse group LASSO was applied to estimation of the eigenphone matrix.The weight of the SGL norm was adjusted to control the complexity of the adaptation model.Finally,an accelerated proximal gradient method was adopted to solve the mathematic optimization.The method was compared with up-to-date norm algorithms.Experiments on an mandarin Chinese continuous speech recognition task show that,the performance of the SGL con-straint eigenphone method can improve remarkably the performance of the system than original eigenphone method,and is also superior to l<sub>1</sub>、l<sub>2</sub>-norm and elastic net constraint methods.
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institution Kabale University
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publisher Editorial Department of Journal on Communications
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spelling doaj-art-dfbd35826d684af080a4585b24c681d42025-01-14T06:53:30ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2015-09-0136475459695277Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognitionDan QUWen-lin ZHANGOriginal eigenphone speaker adaptation method performed well when the amount of adaptation data was suffi-cient.However,it suffered from server overfitting when insufficient amount of adaptation data was provided.A sparse group LASSO(SGL) constraint eigenphone speaker adaptation method was proposed.Firstly,the principle of eigenphone speaker adaptation was introduced in case of hidden Markov model-Gaussian mixture model (HMM-GMM) based speech recognition system.Then,a sparse group LASSO was applied to estimation of the eigenphone matrix.The weight of the SGL norm was adjusted to control the complexity of the adaptation model.Finally,an accelerated proximal gradient method was adopted to solve the mathematic optimization.The method was compared with up-to-date norm algorithms.Experiments on an mandarin Chinese continuous speech recognition task show that,the performance of the SGL con-straint eigenphone method can improve remarkably the performance of the system than original eigenphone method,and is also superior to l<sub>1</sub>、l<sub>2</sub>-norm and elastic net constraint methods.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2015241/speaker adaptationeigenphonegroup sparse constraintsparse group LASSO constraintproximal gradient method
spellingShingle Dan QU
Wen-lin ZHANG
Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition
Tongxin xuebao
speaker adaptation
eigenphone
group sparse constraint
sparse group LASSO constraint
proximal gradient method
title Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition
title_full Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition
title_fullStr Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition
title_full_unstemmed Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition
title_short Sparse group LASSO constraint eigenphone speaker adaptation method for speech recognition
title_sort sparse group lasso constraint eigenphone speaker adaptation method for speech recognition
topic speaker adaptation
eigenphone
group sparse constraint
sparse group LASSO constraint
proximal gradient method
url http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2015241/
work_keys_str_mv AT danqu sparsegrouplassoconstrainteigenphonespeakeradaptationmethodforspeechrecognition
AT wenlinzhang sparsegrouplassoconstrainteigenphonespeakeradaptationmethodforspeechrecognition