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Multi-Source Neural Model for Machine Translation of Agglutinative Language
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In: Future Internet ; Volume 12 ; Issue 6 (2020)
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A High Efficient Biological Language Model for Predicting Protein–Protein Interactions
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In: Cells ; Volume 8 ; Issue 2 (2019)
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Punctuation and Parallel Corpus Based Word Embedding Model for Low-Resource Languages
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In: Information ; Volume 11 ; Issue 1 (2019)
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Constructing Uyghur Commonsense Knowledge Base by Knowledge Projection
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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The ingredients of comparison: The semantics of the excessive construction in Japanese
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In: Semantics and Pragmatics, Vol 8, Iss 0, Pp 1-38 (2015) (2015)
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Machine Learning Paradigms for Speech Recognition: An Overview
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Sequence Clustering and Labeling for Unsupervised Query Intent Discovery
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In: http://www.cs.utoronto.ca/%7Ejcheung/papers/wsdm2012.pdf (2012)
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Understanding the semantic structure of noun phrase queries
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In: http://research.microsoft.com/pubs/130815/acl.pdf (2010)
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Semi-supervised learning of semantic classes for query . . .
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In: http://research.microsoft.com/pubs/101154/fp0894-wang-webpost.pdf (2009)
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Rejoinder: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies
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The Vocal Joystick data collection effort and vowel corpus
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In: http://ssli.ee.washington.edu/people/bilmes/mypapers/VJ_ICSLP_2006_v8.pdf (2006)
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The Vocal Joystick: A voice-based humancomputer interface for individuals with motor impairments
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In: https://www.ee.washington.edu/techsite/papers/documents/UWEETR-2005-0007.pdf (2005)
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The Vocal Joystick Demo at UIST05: A Voice-Based Human-Computer Interface
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In: http://ssli.ee.washington.edu/vj/files/UIST-demo-abstract.pdf (2005)
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Algorithms for data-driven ASR parameter quantization
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In: http://ssli.ee.washington.edu/people/bilmes/mypapers/quan-algo-csl-sdarticle.pdf (2005)
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The Vocal Joystick: A Voice-Based Human-Computer Interface for Individuals with Motor Impairments
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In: http://ssli.ee.washington.edu/people/bilmes/mypapers/uist05.pdf (2005)
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Abstract:
We describe the technical details behind a novel voicebased human-computer interface designed to enable individuals with motor impairments to use vocal parameters for both discrete and continuous control tasks. Since discrete spoken commands are not ideally suited to such tasks, our methodology exploits a large set of continuous acoustic-phonetic parameters like pitch, loudness, vowel quality, etc. Their selection is optimized with respect to automatic recognizability, communication bandwidth, learnability, suitability, and ease of use. These parameters are extracted continually in real time, transformed via adaptation and acceleration, and converted into continuous control signals. 1
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URL: http://ssli.ee.washington.edu/people/bilmes/mypapers/uist05.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.76.115
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Algorithms for Data-Driven ASR Parameter Quantization
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In: http://ssli.ee.washington.edu/people/karim/papers/quan-algorithms.pdf (2003)
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A Phrase Table Filtering Model Based on Binary Classification for Uyghur-Chinese Machine Translation
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In: http://www.jcomputers.us/vol9/jcp0912-02.pdf
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18 |
General Terms
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In: http://dub.washington.edu/pubs/assets2006/assets71-harada.pdf
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LEXICON MODELING FOR QUERY UNDERSTANDING
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In: http://groups.csail.mit.edu/sls/publications/2011/Liu_ICASSP2011.pdf
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Understanding the semantic structure of noun phrase queries. ACL’10
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In: http://aclweb.org/anthology-new/P/P10/P10-1136.pdf
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