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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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| 2 |
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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| 3 |
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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| 4 |
Constructing Uyghur Commonsense Knowledge Base by Knowledge Projection
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In: Applied Sciences ; Volume 9 ; Issue 16 (2019)
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| 5 |
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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| 6 |
Machine Learning Paradigms for Speech Recognition: An Overview
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| 7 |
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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| 8 |
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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| 9 |
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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| 10 |
Rejoinder: Quantifying the Fraction of Missing Information for Hypothesis Testing in Statistical and Genetic Studies
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| 11 |
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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| 12 |
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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| 13 |
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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| 14 |
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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| 15 |
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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| 16 |
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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| 17 |
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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Abstract:
Mouse control has become a crucial aspect of many modern day computer interactions. This poses a challenge for individuals with motor impairments or those whose use of hands are restricted due to situational constraints. We present a system called the Vocal Joystick which allows the user to continuously control the mouse cursor by varying vocal parameters such as vowel quality, loudness and pitch. A survey of existing cursor control methods is presented to highlight the key characteristics of the Vocal Joystick. Evaluations were conducted to characterize expert performance capability of the Vocal Joystick, and to compare novice user performance and preference for the Vocal Joystick and two other existing speech based cursor control methods. Our results show that Fitts ’ law is a good predictor of the speedaccuracy tradeoff for the Vocal Joystick, and suggests that the optimal performance of the Vocal Joystick may be comparable to that of a conventional hand-operated joystick. Novice user evaluations show that the Vocal Joystick can be used by people without extensive training, and that it presents a viable alternative to existing speech-based cursor control methods. Categories and Subject Descriptors H.5.2 [Information interfaces and presentation]: User interfaces—Voice I/O; K.4.2 [Computers and Society]:
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Keyword:
continuous; cursor control; Fitts’ law; Human Factors; Measurement; Performance Keywords Voice-based interface; speech recognition
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URL: http://dub.washington.edu/pubs/assets2006/assets71-harada.pdf
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.102.9903
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| 19 |
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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| 20 |
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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