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1
Multilingual Graphemic Hybrid ASR with Massive Data Augmentation ...
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2
From Senones to Chenones: Tied Context-Dependent Graphemes for Hybrid Speech Recognition ...
Le, Duc; Zhang, Xiaohui; Zheng, Weiyi. - : arXiv, 2019
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3
Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning ...
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4
Language Models for Image Captioning: The Quirks and What Works ...
Devlin, Jacob; Cheng, Hao; Fang, Hao. - : arXiv, 2015
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5
From Captions to Visual Concepts and Back ...
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6
Broadcast News Lattices
Zweig, Geoffrey; Karakos, Damianos; Nguyen, Patrick. - : Linguistic Data Consortium, 2011. : https://www.ldc.upenn.edu, 2011
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7
Broadcast News Lattices ...
Zweig, Geoffrey; Karakos, Damianos; Nguyen, Patrick. - : Linguistic Data Consortium, 2011
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8
Empirical Properties of Multilingual Phone-To-Word Transduction
In: DTIC (2008)
Abstract: This paper explores the error-robustness of phone-to-word transduction across a variety of languages. We implement a noisy channel model in which a phonetic input stream is corrupted by an error model, and then transduced back to words using the inverse error model and linguistic constraints. By controlling the error level, we are able to measure the sensitivity of different languages to degradation in the phonetic input stream. This analysis is carried further to measure the importance of each phone in each language individually. We study Arabic, Chinese, English, German and Spanish, and find that they behave similarly in this paradigm: in each case, a phone error produces about 1.4 word errors, and frequently incorrect phones matter slightly less than others. In the absence of phone errors, transduced word errors are still present, and we use the conditional entropy of words given phones to explain the observed behavior. ; See also ADM002091. Presented at the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008) held in Las Vegas, Nevada on March 30-April 4, 2008. Published in the Proceedidngs of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP 2008) p4445-4448, 2008.
Keyword: *MULTILINGUAL; *SPEECH RECOGNITION; *TRANSDUCTION; ASR(AUTOMATIC SPEECH RECOGNTION); DECODING; DEGRADATION; Electrical and Electronic Equipment; ENTROPY; ERRORS; INVERSION; Linguistics; MODELS; PHONETICS; SENSITIVITY; SYMPOSIA; WORDS(LANGUAGE)
URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA509700
http://www.dtic.mil/docs/citations/ADA509700
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9
Advances in speech transcription at IBM under the DARPA EARS program
In: Institute of Electrical and Electronics Engineers. IEEE transactions on audio, speech and language processing. - New York, NY : Inst. 14 (2006) 5, 1596-1608
BLLDB
OLC Linguistik
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10
On data mining of speech, audio, and dialog
Gilbert, Mazin (Hrsg.); Moore, Roger K. (Hrsg.); Zweig, Geoffrey (Hrsg.). - New York, NY : Inst. of Electrical and Electronic Engineers, 2005
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11
Arc minimization in finite-state decoding graphs with cross-word acoustic context
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 18 (2004) 4, 397-415
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12
Arc minimization in finite-state decoding graphs with cross-word acoustic context
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 18 (2004) 4, 397-416
OLC Linguistik
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13
Bayesian network structures and inference techniques for automatic speech recognition
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 17 (2003) 2, 173-194
OLC Linguistik
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14
New computational paradigms for acoustic modeling in speech recognition
Russell, Martin J. (Hrsg.); Bilmes, Jeff A. (Hrsg.); Lefevre, Fabrice (Mitarb.)...
In: Computer speech and language. - Amsterdam [u.a.] : Elsevier 17 (2003) 2-3, 107-305
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15
Compositional Modeling with DPNs
In: DTIC AND NTIS (1998)
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