Searching for authors named "Min Tang" – sorted by Relevance.
10 documents found, showing 1 through 10.
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Large vocabulary continuous speech recognition using linguistic features and constraints
- … Recognition Using Linguistic Features and Constraints by Min Tang Submitted to the Department of Electrical…
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Finding strong pseudoprimes to several bases. II,Math
- … ZHENXIANG ZHANG AND MIN TANG holds for every b with gcd(n, b) = 1. If (1.1) holds, then we say that n passes…
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Active Learning for Statistical Natural Language Parsing
- …Active Learning for Statistical Natural Language Parsing Min Tang Spoken Language Systems Group…
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ON A UNIFORMLY SECOND ORDER NUMERICAL METHOD FOR THE ONE-DIMENSIONAL DISCRETE-ORDINATE TRANSPORT EQUATION AND ITS DIFFUSION LIMIT WITH INTERFACE ∗
- … EQUATION AND ITS DIFFUSION LIMIT WITH INTERFACE ∗ SHI JIN † , MIN TANG ‡ , AND HOUDE HAN § Abstract…
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Voice Transformations: From Speech Synthesis to Mammalian Vocalizations
- …Voice Transformations: From Speech Synthesis to Mammalian Vocalizations Min Tang, Chao Wang…
- Cited by 5 (1 self) – Add To MetaCart
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Active Learning for Statistical Natural Language Parsing
- …Active Learning for Statistical Natural Language Parsing Min Tang Spoken Language Systems Group…
- Cited by 18 (0 self) – Add To MetaCart
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Modeling Linguistic Features in Speech Recognition
- …-133982 and by NTT, and by an industrial consortium supporting the Spoken Language Systems group. Min Tang, Stephanie…
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A Solid Model Based Virtual Hairy Brush
- …A Solid Model Based Virtual Hairy Brush SONGHUA XU � ,MIN TANG ,FRANCIS C.M. LAU, £ AND YUN-HE PAN…
- Cited by 9 (4 self) – Add To MetaCart
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Volume xx (200y), Number z, pp. 1--11
- …Volume xx (200y), Number z, pp. 1–11 A Solid Model Based Virtual Hairy Brush Songhua Xu 1�2 Min…
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Combining Linguistic Knowledge and Acoustic Information in Automatic Pronunciation Lexicon Generation
- … Generation Grace Chung Ý , Chao WangÞ, Stephanie SeneffÞ, EdFiliskoÞ, Min TangÞ ÝCorporation for National…
- Cited by 6 (2 self) – Add To MetaCart
Showing 1 through 10.
