{"id":4520,"date":"2020-06-23T16:24:43","date_gmt":"2020-06-23T08:24:43","guid":{"rendered":"http:\/\/pairlabs.ai.pro6.designworks.tw\/?post_type=portfolio&#038;p=4520"},"modified":"2020-07-22T14:53:40","modified_gmt":"2020-07-22T06:53:40","slug":"deep-intelligence-based-spoken-language-processing-p-en","status":"publish","type":"portfolio","link":"https:\/\/pairlabs.ai\/en\/portfolio-item\/deep-intelligence-based-spoken-language-processing-p-en\/","title":{"rendered":"Deep Intelligence Based Spoken Language Processing"},"content":{"rendered":"<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_1' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-small-hide av-mini-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4520'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:20px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h1 style=\"text-align: center;\">Natural Language Application Team<\/h1>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_1' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4520'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_2' class='avia-section main_color avia-section-large avia-no-border-styling avia-full-stretch av-section-color-overlay-active avia-bg-style-fixed    av-desktop-hide av-medium-hide container_wrap sidebar_right' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  '  data-section-bg-repeat='stretch' style='background-repeat: no-repeat; background-image: url(https:\/\/pairlabs.ai\/wp-content\/uploads\/2020\/05\/wall005.jpg);background-attachment: fixed; background-position: bottom right;  ' ><div class='av-section-color-overlay-wrap'><div class='av-section-color-overlay' style='opacity: 0.6; background-color: #ffffff; '><\/div><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4520'><div class='entry-content-wrapper clearfix'>\n<div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class=\"flex_column av_one_fourth  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding first   \" style='border-radius:0px; '><\/div><\/div><!--close column table wrapper. Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' style='margin-top:0px; margin-bottom:-20px; '><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top av-zero-column-padding   \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '  style='font-size:20px; '  itemprop=\"text\" ><p style=\"text-align: center;\">Pervasive Artificial Intelligence Research (PAIR) Labs<\/p>\n<\/div><\/section><br \/>\n<div style='height:1px' class='hr hr-invisible   '><span class='hr-inner ' ><span class='hr-inner-style'><\/span><\/span><\/div><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 --><div class='flex_column_table av-equal-height-column-flextable -flextable' ><div class='av-flex-placeholder'><\/div><div class=\"flex_column av_one_half  flex_column_table_cell av-equal-height-column av-align-top    \" style='background-color:#00a0e9; background:linear-gradient(to bottom right,#00a0e9,#25a98f); padding:10px; border-radius:0px; '><p><div style=' margin-top:-21px; margin-bottom:0px;'  class='hr hr-custom hr-center hr-icon-yes   '><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><span class='av-seperator-icon' style='color:#ffffff;' aria-hidden='true' data-av_icon='\ue883' data-av_iconfont='entypo-fontello'><\/span><span class='hr-inner   inner-border-av-border-thin' style=' width:0px;' ><span class='hr-inner-style'><\/span><\/span><\/div><br \/>\n<section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  av_inherit_color '  style='font-size:30px; color:#ffffff; '  itemprop=\"text\" ><h2 style=\"text-align: center;\">Natural Language Application Team<\/h2>\n<\/div><\/section><\/p><\/div><\/div><!--close column table wrapper. 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Autoclose: 1 -->\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><\/div><div id='after_section_2' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4520'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_3' class='avia-section socket_color avia-section-default avia-no-border-styling avia-bg-style-scroll    av-arrow-down-section container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4520'><div class='entry-content-wrapper clearfix'>\n<div style='padding-bottom:0px; margin:0 0 0 0; font-size:30px;' class='av-special-heading av-special-heading-h3  blockquote modern-quote modern-centered   av-inherit-size '><h3 class='av-special-heading-tag '  itemprop=\"headline\"  >Deep Intelligence Based Spoken Language Processing<\/h3><div class='special-heading-border'><div class='special-heading-inner-border' ><\/div><\/div><\/div>\n<\/div><\/div><\/div><!-- close content main div --><\/div><div class='av-extra-border-element border-extra-arrow-down'><div class='av-extra-border-outer'><div class='av-extra-border-inner'  style='background-color:#333333;' ><\/div><\/div><\/div><\/div><div id='after_section_3' class='main_color av_default_container_wrap container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4520'><div class='entry-content-wrapper clearfix'>\n<\/div><\/div><\/div><!-- close content main div --><\/div><\/div><div id='av_section_4' class='avia-section main_color avia-section-default avia-no-border-styling avia-bg-style-scroll   container_wrap sidebar_right' style=' '   style=' ' ><div class='container' ><div class='template-page content  av-content-small alpha units'><div class='post-entry post-entry-type-page post-entry-4520'><div class='entry-content-wrapper clearfix'>\n<div class=\"flex_column av_three_fifth  flex_column_div av-zero-column-padding first  \" style='border-radius:0px; '><section class=\"av_textblock_section \"  itemscope=\"itemscope\" itemtype=\"https:\/\/schema.org\/CreativeWork\" ><div class='avia_textblock  '   itemprop=\"text\" ><p><b>Principal Investigator:\u00a0<\/b><a href=\"http:\/\/pairlabs.ai\/\/en\/2018\/04\/21\/professor-jia-ching-wang\/\">Professor Jia-Ching Wang<\/a><\/p>\n<p>&#8211;<\/p>\n<blockquote>\n<h5><b>Summary<\/b><\/h5>\n<\/blockquote>\n<p>Speech is not only the most natural means of communications among people but also the most effective means of human-computer interaction. Enabling a computer to process spoken language like a human is a great problem, which scholars have been trying to solve for decades. Deep leaning puts this goal into practice. To such an end, this project develops a plan for processing spoken language that integrates speech processing, acoustic signal processing, natural language processing, and deep learning techniques. Key techniques such as intelligent multi-channel speech processing and speech separation, robust speech recognition, spoken language translation, speech emotion recognition, and open field dialogue will be developed. Native languages and dialects such as Minnan are particularly addressed.<\/p>\n<blockquote>\n<h5><b>Keywords<\/b><\/h5>\n<\/blockquote>\n<p>Spoken language processing, speech separation, speech recognition, spoken language translation, speech emotion recognition, dialogue system, deep learning<\/p>\n<blockquote>\n<h5><b>Innovations<\/b><\/h5>\n<\/blockquote>\n<ul>\n<li>In front-end processing, we propose a deep learning-based multi-channel speech enhancement algorithm, which integrates the beamforming technique and the deep neural networks.<\/li>\n<li>For speech separation, we present a GP regression-based SCSS model. The estimated source is measured by the predictive mean of GP regression models, and the hyper-parameter learning process is executed by using the nonlinear conjugate gradient algorithm.<\/li>\n<li>We propose the hierarchical extreme learning machine (HELM) for audio-visual speech enhancement as an alternative model for the speech enhancement task.<\/li>\n<li>To achieve robust speech recognition, we propose a novel use of the graph-regularization based methods to enhance speech features by preserving the inherent manifold structures of the magnitude modulation spectra and excluding irrelevant ones.<\/li>\n<li>For native language speech recognition, we have developed a Taiwanese Minnan speech recognizer.<\/li>\n<li>In machine translation, we present a bi-directional translator between English and Chinese.<\/li>\n<li>We propose an acoustic speech emotion recognition system, which uses multiple feature extraction network based on deep learning, as well as a new recurrent neural network that we have developed.<\/li>\n<li>In order to understand the semantics of the dialogue, we develop language understanding techniques for dialogue systems.<\/li>\n<\/ul>\n<h5><b>Benefits<\/b><\/h5>\n<ul>\n<li>This project develops an English learning robot based on ASUS Zenbo. Through intelligent speech recognition technology, the English learning robot enables the user to practice pronunciation and articulation within non-English environments.<\/li>\n<li>The robustness techniques alleviate the undesired impact caused by environmental distortions so as to make automatic speech recognition systems maintain an acceptable performance level.<\/li>\n<li>The spoken language processing techniques that are developed herein will be used on an intelligent interactive plat-form that can be applied to real-world applications.<\/li>\n<\/ul>\n<\/div><\/section><\/div><div class=\"flex_column av_two_fifth  flex_column_div av-zero-column-padding   \" style='border-radius:0px; '><p><div class='avia-progress-bar-container  av-desktop-hide av-medium-hide av-small-hide av-mini-hide avia_animate_when_almost_visible   av-striped-bar av-animated-bar '><div class='avia-progress-bar theme-color-bar icon-bar-no'><div class='progressbar-title-wrap'><div class='progressbar-icon'><span 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