Proceedings of the IEEE

Issue 5 • May 2013

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Displaying Results 1 - 22 of 22
  • Front cover

    Publication Year: 2013, Page(s): C1
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  • Proceedings of the IEEE publication information

    Publication Year: 2013, Page(s): C2
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  • Table of contents

    Publication Year: 2013, Page(s):1029 - 1030
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  • Cyber-Eco Technology: Engineering of Ecological Systems [Point of View]

    Publication Year: 2013, Page(s):1031 - 1033
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  • Speech Information Processing: Theory and Applications [Scanning the Issue]

    Publication Year: 2013, Page(s):1034 - 1037
    Cited by:  Papers (5)
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  • Acoustic Analysis for Automatic Speech Recognition

    Publication Year: 2013, Page(s):1038 - 1053
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (255 KB) | HTML iconHTML

    As a pattern recognition application, automatic speech recognition (ASR) requires the extraction of useful features from its input signal, speech. To help determine relevance, human speech production and acoustic aspects of speech perception are reviewed, to identify acoustic elements likely to be most important for ASR. Common methods of estimating useful aspects of speech spectral envelopes are ... View full abstract»

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  • Conditional Random Fields in Speech, Audio, and Language Processing

    Publication Year: 2013, Page(s):1054 - 1075
    Cited by:  Papers (6)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (749 KB) | HTML iconHTML

    Conditional random fields (CRFs) are probabilistic sequence models that have been applied in the last decade to a number of applications in audio, speech, and language processing. In this paper, we provide a tutorial overview of CRF technologies, pointing to other resources for more in-depth discussion; in particular, we describe the common linear-chain model as well as a number of common extensio... View full abstract»

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  • Multistream Recognition of Speech: Dealing With Unknown Unknowns

    Publication Year: 2013, Page(s):1076 - 1088
    Cited by:  Papers (9)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (402 KB) | HTML iconHTML

    The paper discusses an approach for dealing with unexpected acoustic elements in speech. The approach is motivated by observations of human performance on such problems, which indicate the existence of multiple parallel processing streams in the human speech processing cognitive system, combined with the human ability to know when the correct information is being received. Some earlier relevant en... View full abstract»

    Open Access
  • An Information-Extraction Approach to Speech Processing: Analysis, Detection, Verification, and Recognition

    Publication Year: 2013, Page(s):1089 - 1115
    Cited by:  Papers (14)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2541 KB) | HTML iconHTML

    The field of automatic speech recognition (ASR) has enjoyed more than 30 years of technology advances due to the extensive utilization of the hidden Markov model (HMM) framework and a concentrated effort by the speech community to make available a vast amount of speech and language resources, known today as the Big Data Paradigm. State-of-the-art ASR systems achieve a high recognition accuracy for... View full abstract»

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  • Speech-Centric Information Processing: An Optimization-Oriented Approach

    Publication Year: 2013, Page(s):1116 - 1135
    Cited by:  Papers (11)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (507 KB) | HTML iconHTML

    Automatic speech recognition (ASR) is a central and common component of voice-driven information processing systems in human language technology, including spoken language translation (SLT), spoken language understanding (SLU), voice search, spoken document retrieval, and so on. Interfacing ASR with its downstream text-based processing tasks of translation, understanding, and information retrieval... View full abstract»

    Open Access
  • Spoken Language Recognition: From Fundamentals to Practice

    Publication Year: 2013, Page(s):1136 - 1159
    Cited by:  Papers (48)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (2069 KB) | HTML iconHTML

    Spoken language recognition refers to the automatic process through which we determine or verify the identity of the language spoken in a speech sample. We study a computational framework that allows such a decision to be made in a quantitative manner. In recent decades, we have made tremendous progress in spoken language recognition, which benefited from technological breakthroughs in related are... View full abstract»

    Open Access
  • POMDP-Based Statistical Spoken Dialog Systems: A Review

    Publication Year: 2013, Page(s):1160 - 1179
    Cited by:  Papers (33)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (658 KB) | HTML iconHTML

    Statistical dialog systems (SDSs) are motivated by the need for a data-driven framework that reduces the cost of laboriously handcrafting complex dialog managers and that provides robustness against the errors created by speech recognizers operating in noisy environments. By including an explicit Bayesian model of uncertainty and by optimizing the policy via a reward-driven process, partially obse... View full abstract»

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  • Statistical Machine Translation for Speech: A Perspective on Structures, Learning, and Decoding

    Publication Year: 2013, Page(s):1180 - 1202
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1337 KB) | HTML iconHTML

    In this paper, we survey and analyze state-of-the-art statistical machine translation (SMT) techniques for speech translation (ST). We review key learning problems, and investigate essential model structures in SMT, taking a unified perspective to reveal both connections and contrasts between automatic speech recognition (ASR) and SMT. We show that phrase-based SMT can be viewed as a sequence of f... View full abstract»

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  • Behavioral Signal Processing: Deriving Human Behavioral Informatics From Speech and Language

    Publication Year: 2013, Page(s):1203 - 1233
    Cited by:  Papers (37)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3175 KB) | HTML iconHTML

    The expression and experience of human behavior are complex and multimodal and characterized by individual and contextual heterogeneity and variability. Speech and spoken language communication cues offer an important means for measuring and modeling human behavior. Observational research and practice across a variety of domains from commerce to healthcare rely on speech- and language-based inform... View full abstract»

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  • Speech Synthesis Based on Hidden Markov Models

    Publication Year: 2013, Page(s):1234 - 1252
    Cited by:  Papers (54)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1154 KB) | HTML iconHTML

    This paper gives a general overview of hidden Markov model (HMM)-based speech synthesis, which has recently been demonstrated to be very effective in synthesizing speech. The main advantage of this approach is its flexibility in changing speaker identities, emotions, and speaking styles. This paper also discusses the relation between the HMM-based approach and the more conventional unit-selection ... View full abstract»

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  • Underwater Cables

    Publication Year: 2013, Page(s):1253 - 1259
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    Reports on the technologies that comprise underwater cables, examines their historical development, discusses their deployment, and reports on new areas of technological development to support undersea communciations. View full abstract»

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  • Future special issues/special sections of the Proceedings

    Publication Year: 2013, Page(s):1260 - 1261
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  • IEEE Member Digital Library

    Publication Year: 2013, Page(s): 1262
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  • Open Access

    Publication Year: 2013, Page(s): 1263
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  • IEEE Xplore Digital Library

    Publication Year: 2013, Page(s): 1264
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  • IEEE Global History Network

    Publication Year: 2013, Page(s): C3
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  • Coming next month in the June issue of our journal ... [back cover]

    Publication Year: 2013, Page(s): C4
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Meet Our Editors

Editor-in-Chief
H. Joel Trussell
North Carolina State University