The Experts below are selected from a list of 315 Experts worldwide ranked by ideXlab platform
Cai Lianhong - One of the best experts on this subject based on the ideXlab platform.
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Design of A Research Platform of Digital Speech Processing
Computer Engineering, 2006Co-Authors: Cai LianhongAbstract:This paper presents a new research platform for visualization of digital Speech,which supports multi-view and multi data interface.The modules-combined architecture,employed in the platform,makes new algorithm of Speech Processing can be quickly embedded.All modules are classified inner modules and extra modules.Data interface and visualization of Speech are integrated into inner modules,while analysis procedures are implemented in the extra modules.Vertically arranged in a window,the results of algorithms and procedures can be easily compared and analyzed.The presented platform also includes built-in Speech XML-based labeling module.Hence,it can be used in the building process of corpus and other fields of Speech Processing.
Ronald W. Schafer - One of the best experts on this subject based on the ideXlab platform.
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ICASSP - Matlab exercises in support of teaching digital Speech Processing
2014 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2014Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:This paper describes a set of 58 Matlab ® -based Speech Processing exercises designed to give students and instructors hands-on experience with digital Speech Processing basics, fundamentals, representations, algorithms and applications. This result is achieved by providing working Matlab code using a LITE graphical user interface (GUI) for ease of use and understanding of the code. For each Matlab exercise we provide a brief description of the code and GUI structure, an explanation of key technical aspects of the solution, a description of the organization of the Lite Graphical User Interface, a scripted run of the software with an extensive set of Speech files for Processing, some results figures generated by the provided code, and a set of technical issues for further experimentation with the code. Our goal with these exercises is to provide a set of Speech Processing tools for the instructor and an extended set of Speech Processing exercises (denoted as “Issues for Further Experimentation”) that students can use to develop their understanding of the technical content of each Speech Processing exercise. This paper describes the resulting set of exercises and shows how they can be used to enhance the teaching and learning of digital Speech Processing.
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Programs for supporting the teaching of digital Speech Processing
2013 IEEE Digital Signal Processing and Signal Processing Education Meeting (DSP SPE), 2013Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:This paper describes a set of about 60 MATLAB®-based Speech Processing exercises designed to give students and instructors hands-on experience with digital Speech Processing algorithms and systems. This result is achieved by providing MATLAB code with a graphical user interface (GUI) for ease of use and understanding of the code. For each MATLAB exercise we provide a description of the code and GUI structure, an explanation of key technical aspects of the solution, a description of the organization of the Lite Graphical User Interface,1 a scripted run of the software with an extensive set of Speech files for Processing, one or more results figures generated by the provided code, and a set of technical issues for further experimentation with the code. Our goal with these exercises was to provide a useful and unique set of Speech Processing tools for the instructor and a set of Speech Processing exercises (denoted as “Issues for Further Experimentation”) that students can use to develop their understanding of the relevant technical content of each Speech Processing exercise. This paper describes the resulting set of Speech Processing exercises and shows how they can be used to enhance the teaching of digital Speech Processing.
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Theory and Applications of Digital Speech Processing
2010Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:Theory and Applications of Digital Speech Processing is ideal for graduate students in digital signal Processing, and undergraduate students in Electrical and Computer Engineering. With its clear, up-to-date, hands-on coverage of digital Speech Processing, this text is also suitable for practicing engineers in Speech Processing. This new text presents the basic concepts and theories of Speech Processing with clarity and currency, while providing hands-on computer-based laboratory experiences for students. The material is organized in a manner that builds a strong foundation of basics first, and then concentrates on a range of signal Processing methods for representing and Processing the Speech signal.
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Introduction to digital Speech Processing
Foundations and Trends in Signal Processing, 2007Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:Since even before the time of Alexander Graham Bell�s revolution- ary invention, engineers and scientists have studied the phenomenon of Speech communication with an eye on creating more e?cient and e?ective systems of human-to-human and human-to-machine communi- cation. Starting in the 1960s, digital signal Processing (DSP), assumed a central role in Speech studies, and today DSP is the key to realizing the fruits of the knowledge that has been gained through decades of research. Concomitant advances in integrated circuit technology and computer architecture have aligned to create a technological environ- ment with virtually limitless opportunities for innovation in Speech communication applications. In this text, we highlight the central role of DSP techniques in modern Speech communication research and appli- cations. We present a comprehensive overview of digital Speech process- ing that ranges from the basic nature of the Speech signal, through a variety of methods of representing Speech in digital form, to applica- tions in voice communication and automatic synthesis and recognition of Speech. The breadth of this subject does not allow us to discuss anyaspect of Speech Processing to great depth; hence our goal is to pro- vide a useful introduction to the wide range of important concepts that comprise the ?eld of digital Speech Processing. A more comprehensive treatment will appear in the forthcoming book, Theory and Application of Digital Speech Processing [101].
Lawrence R. Rabiner - One of the best experts on this subject based on the ideXlab platform.
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ICASSP - Matlab exercises in support of teaching digital Speech Processing
2014 IEEE International Conference on Acoustics Speech and Signal Processing (ICASSP), 2014Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:This paper describes a set of 58 Matlab ® -based Speech Processing exercises designed to give students and instructors hands-on experience with digital Speech Processing basics, fundamentals, representations, algorithms and applications. This result is achieved by providing working Matlab code using a LITE graphical user interface (GUI) for ease of use and understanding of the code. For each Matlab exercise we provide a brief description of the code and GUI structure, an explanation of key technical aspects of the solution, a description of the organization of the Lite Graphical User Interface, a scripted run of the software with an extensive set of Speech files for Processing, some results figures generated by the provided code, and a set of technical issues for further experimentation with the code. Our goal with these exercises is to provide a set of Speech Processing tools for the instructor and an extended set of Speech Processing exercises (denoted as “Issues for Further Experimentation”) that students can use to develop their understanding of the technical content of each Speech Processing exercise. This paper describes the resulting set of exercises and shows how they can be used to enhance the teaching and learning of digital Speech Processing.
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Programs for supporting the teaching of digital Speech Processing
2013 IEEE Digital Signal Processing and Signal Processing Education Meeting (DSP SPE), 2013Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:This paper describes a set of about 60 MATLAB®-based Speech Processing exercises designed to give students and instructors hands-on experience with digital Speech Processing algorithms and systems. This result is achieved by providing MATLAB code with a graphical user interface (GUI) for ease of use and understanding of the code. For each MATLAB exercise we provide a description of the code and GUI structure, an explanation of key technical aspects of the solution, a description of the organization of the Lite Graphical User Interface,1 a scripted run of the software with an extensive set of Speech files for Processing, one or more results figures generated by the provided code, and a set of technical issues for further experimentation with the code. Our goal with these exercises was to provide a useful and unique set of Speech Processing tools for the instructor and a set of Speech Processing exercises (denoted as “Issues for Further Experimentation”) that students can use to develop their understanding of the relevant technical content of each Speech Processing exercise. This paper describes the resulting set of Speech Processing exercises and shows how they can be used to enhance the teaching of digital Speech Processing.
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Theory and Applications of Digital Speech Processing
2010Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:Theory and Applications of Digital Speech Processing is ideal for graduate students in digital signal Processing, and undergraduate students in Electrical and Computer Engineering. With its clear, up-to-date, hands-on coverage of digital Speech Processing, this text is also suitable for practicing engineers in Speech Processing. This new text presents the basic concepts and theories of Speech Processing with clarity and currency, while providing hands-on computer-based laboratory experiences for students. The material is organized in a manner that builds a strong foundation of basics first, and then concentrates on a range of signal Processing methods for representing and Processing the Speech signal.
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Introduction to digital Speech Processing
Foundations and Trends in Signal Processing, 2007Co-Authors: Lawrence R. Rabiner, Ronald W. SchaferAbstract:Since even before the time of Alexander Graham Bell�s revolution- ary invention, engineers and scientists have studied the phenomenon of Speech communication with an eye on creating more e?cient and e?ective systems of human-to-human and human-to-machine communi- cation. Starting in the 1960s, digital signal Processing (DSP), assumed a central role in Speech studies, and today DSP is the key to realizing the fruits of the knowledge that has been gained through decades of research. Concomitant advances in integrated circuit technology and computer architecture have aligned to create a technological environ- ment with virtually limitless opportunities for innovation in Speech communication applications. In this text, we highlight the central role of DSP techniques in modern Speech communication research and appli- cations. We present a comprehensive overview of digital Speech process- ing that ranges from the basic nature of the Speech signal, through a variety of methods of representing Speech in digital form, to applica- tions in voice communication and automatic synthesis and recognition of Speech. The breadth of this subject does not allow us to discuss anyaspect of Speech Processing to great depth; hence our goal is to pro- vide a useful introduction to the wide range of important concepts that comprise the ?eld of digital Speech Processing. A more comprehensive treatment will appear in the forthcoming book, Theory and Application of Digital Speech Processing [101].
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Telecommunications Applications of Speech Processing
Speech Recognition and Coding, 1995Co-Authors: Lawrence R. RabinerAbstract:The ways in which people communicate are changing rapidly. The standard voice call over a wired network is but one means of communications, which already includes cordless and wireless voice calls, video calls, beeper service, FAX service, e-mail service, and data services. This revolution in communications is being fueled by several sources, including the availability of low cost, low power, computation in both DSP and RISC chips, larger and cheaper memory chips, improved algorithms for communications (e.g. modems, signalling) and signal Processing, and finally the creation of world-wide standards for transmission, signal compression, and communication protocols. The broad goal of the communications revolution is to provide seamless and high quality communications between people (or groups of people), anywhere, anytime, and at a reasonable price. Although there are many technologies that form the bases for the communications environment of the twenty-first century, one of the key technologies for making the vision a reality is Speech Processing. In this paper we attempt to show, by example, how Speech Processing has been applied to specific problems in telecommunications, and how it will grow to become an even more essential component of the communications systems of the twenty-first century.
Liu Runsheng - One of the best experts on this subject based on the ideXlab platform.
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Embedded Speech Processing System for Car Wireless Terminals
Computer Engineering, 2005Co-Authors: Liu RunshengAbstract:This paper introduces a novel embedded Speech Processing system, which is implemented in car wireless terminals. This system is composed of two modules: bluetooth module and Speech-Processing module. Through the blue tooth module, car wireless terminal can communicate with cellular phone, download the address book from cellular phone and send it to the Speech Processing module, while the Speech Processing module fulfills Speech recognition, Speech synthesis, Speech coding and system controlling functions. This system can on-line generate the Speech recognition network according to the address book and the recognizable vocabulary scale is up to 1000 words. When the address book includes 600 names, the recognition accuracy rate is more than 97%. The hardware platform of this system is based on SoC architecture and high integration of this architecture makes the system more robust.
Chotiga Pattamadilok - One of the best experts on this subject based on the ideXlab platform.
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The orthographic effects on Speech Processing: beyond the “automaticity vs. strategy” debate.
2016Co-Authors: Chotiga PattamadilokAbstract:Behavioral evidence for the orthographic effects on Speech Processing was first observed in metaphonological tasks more than 30 years ago. This pioneering observation led to a long-standing debate on the automaticity of the effects. In spite of a huge amount of work devoted to tease apart the automatic vs. strategic account of the orthographic influence on Speech Processing, this issue remains difficult to resolve in the context of metaphonological tasks. More recently, many research groups start using spoken word recognition tasks to probe the orthographic effects. This change of experimental paradigm combined with recent data from brain imaging studies have shifted the focus of the debate from the automaticity issue to the cognitive and neural mechanisms underlying the contribution orthography to Speech Processing. During the talk, I will present studies that shed light on this issue. The implication of these findings on Speech Processing models will be discussed.
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Unattentive Speech Processing is influenced by orthographic knowledge: Evidence from mismatch negativity
Brain and Language, 2014Co-Authors: Chotiga Pattamadilok, Cécile Colin, José Morais, Regine KolinskyAbstract:How far can acquired knowledge such as orthographic knowledge affect pre-existing abilities such as Speech perception? This controversial issue was addressed by investigating the automaticity of the influence of orthographic knowledge on Speech Processing. Many studies demonstrated this influence in active, lexico-semantic Speech Processing tasks. However, it has never been observed when Speech is unattended. Here, the Mismatch Negativity (MMN), an automatic index of experience-dependent auditory traces, was recorded in an unattended oddball paradigm manipulating the orthographic congruency between frequent and deviant spoken riming words. Both orthographically congruent and incongruent deviant words elicited a typical MMN over the fronto-central regions, with a stronger response in the incongruent condition. The finding showed that the orthographic dimension of spoken words influences a physiological marker of Speech Processing although participants were required not to attend to the auditory input. This provides evidence for an impact of acquiring a written code on Speech Processing.
