2009 IEEE Workshop on Automatic Speech Recognition & Understanding

13 Nov.-17 Dec. 2009

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  • [USB label]

    Publication Year: 2009, Page(s): 1
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  • Proceedings of the 2009 IEEE Workshop on Automatic Speech Recognition & Understanding [welcome page]

    Publication Year: 2009, Page(s):c1 - c4
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  • Hub page

    Publication Year: 2009, Page(s): 1
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  • Session list

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  • Table of contents

    Publication Year: 2009, Page(s):1 - 12
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  • Author index

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  • Detailed author index

    Publication Year: 2009, Page(s):1 - 42
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  • The end of indexes

    Publication Year: 2009, Page(s): 1
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  • [PDF Reader FAQ and support]

    Publication Year: 2009, Page(s): 1
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  • [PDF Reader FAQ and support]

    Publication Year: 2009, Page(s):1 - 5
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  • [Title page]

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  • Message from the 2009 IEEE ASRU general co-chairs

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  • Org Committee

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  • Scientific committee

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  • Technical review committee

    Publication Year: 2009, Page(s):1 - 2
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  • Generalization problem in ASR acoustic model training and adaptation

    Publication Year: 2009, Page(s):1 - 10
    Cited by:  Papers (4)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1396 KB) | HTML iconHTML

    Since speech is highly variable, even if we have a fairly large-scale database, we cannot avoid the data sparseness problem in constructing automatic speech recognition (ASR) systems. How to train and adapt statistical models using limited amounts of data is one of the most important research issues in ASR. This paper summarizes major techniques that have been proposed to solve the generalization ... View full abstract»

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  • It's not you, it's me: Automatically extracting social meaning from speed dates

    Publication Year: 2009, Page(s): 11
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (62 KB)

    Summary form only given. Automatically detecting human social intentions from spoken conversation is an important task for social computing and for dialogue systems. We describe a system for detecting elements of interactional style: whether a speaker is awkward, friendly, or flirtatious. We create and use a new spoken corpus of 991 4-minute speed-dates. Participants rated themselves and each othe... View full abstract»

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  • Toward machine translation with statistics and syntax and semantics

    Publication Year: 2009, Page(s):12 - 21
    Cited by:  Papers (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (343 KB) | HTML iconHTML

    In this paper, we survey some central issues in the historical, current, and future landscape of statistical machine translation (SMT) research, taking as a starting point an extended three-dimensional MT model space. We posit a socio-geographical conceptual disparity hypothesis, that aims to explain why language pairs like Chinese-English have presented MT with so much more difficulty than others... View full abstract»

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  • Audio-visual automatic speech recognition and related bimodal speech technologies: A review of the state-of-the-art and open problems

    Publication Year: 2009, Page(s): 22
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (77 KB)

    Summary form only given. The presentation will provide an overview of the main research achievements and the state-of-the-art in the area of audiovisual speech processing, mainly focusing in the area of audio-visual automatic speech recognition. The topic has been of interest in the speech research community due to the potential of increased robustness to acoustic noise that the visual modality ho... View full abstract»

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  • Trends and challenges in language modeling for speech recognition and machine translation

    Publication Year: 2009, Page(s): 23
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (55 KB)

    Summary form only given. Language models play an important role in large vocabulary continuous speech recognition (LVCSR) systems and statistical approaches to machine translation (SMT), in particular when modeling morphologically rich languages. Despite intensive research over more than 20 years, state-of-the-art LVCSR and SMT systems seem to use only one dominant approach: n-gram back-off langua... View full abstract»

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  • Manipulation of consonants in natural speech

    Publication Year: 2009, Page(s): 24
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (88 KB)

    Summary form only given - Starting in the 1920s, researchers at AT&T Research characterized speech perception. Until 1950, this work was done by a large group working under Harvey Fletcher, which resulted in the articulation index, an important tool able to predict average speech scores. In the 1950s a dedicated group of researchers at Haskins Labs in NYC attempted to extend these ideas, a... View full abstract»

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  • Spoken dialogue systems: Challenges, and opportunities for research

    Publication Year: 2009, Page(s): 25
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (69 KB)

    Summary form only given. Research into spoken dialog systems has yielded some interesting results recently, such as statistical models for improved robustness, and machine learning for optimal control, among others. What are the basic ideas behind these techniques? What opportunities do they exploit? Are they ready to be deployed in real systems? What remains to be done? This talk aims to tackle t... View full abstract»

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  • Voice-based information retrieval — how far are we from the text-based information retrieval ?

    Publication Year: 2009, Page(s):26 - 43
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (3758 KB) | HTML iconHTML

    Although network content access is primarily text-based today, almost all roles of text can be accomplished by voice. Voice-based information retrieval refers to the situation that the user query and/or the content to be retried are in form of voice. This paper tries to compare the voice-based information retrieval with the currently very successful text-based information retrieval, and identifies... View full abstract»

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  • Acoustic modelling for speech recognition: Hidden Markov models and beyond?

    Publication Year: 2009, Page(s): 44
    Cited by:  Papers (3)  |  Patents (1)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (66 KB)

    Hidden Markov models (HMMs) are still the dominant form of acoustic model used in automatic speech recognition (ASR) systems. However over the years the form, and training, of the HMM for ASR have been extended and modified, so that the current forms used in state-of-the-art speech recognition systems are very different to those originally proposed thirty years ago. This talk will review two of th... View full abstract»

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  • Online discriminative learning: theory and applications

    Publication Year: 2009, Page(s): 45
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (68 KB)

    Summary form only given - Online discriminative learning has been successfully applied to various speech and natural language processing tasks, including classification, parsing, translation and speech recognition/generation. In addition to their simplicity and scalability, online learning algorithms are natural tools in applications involving human-computer interaction, such as computer-assisted ... View full abstract»

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