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First the worst: Finding better gender translations during beam search ...
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USC-SFI MALACH Interviews and Transcripts English – Speech Recognition Edition
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USC-SFI MALACH Interviews and Transcripts English – Speech Recognition Edition ...
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Multi-representation Ensembles and Delayed SGD Updates Improve Syntax-based NMT
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Saunders, Danielle; Stahlberg, Felix; De Gispert, Adrià. - : Association for Computational Linguistics, 2018. : https://aclanthology.info/volumes/proceedings-of-the-56th-annual-meeting-of-the-association-for-computational-linguistics-volume-2-short-papers, 2018. : Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), 2018
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Neural Machine Translation Decoding with Terminology Constraints
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Hasler, eva; de Gspert, Adrià; Iglesias, Gonzalo. - : Association for Computational Linguistics, 2018. : https://aclanthology.coli.uni-saarland.de/volumes/proceedings-of-the-2018-conference-of-the-north-american-chapter-of-the-association-for-computational-linguistics-human-language-technologies-volume-2-short-papers, 2018
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SGNMT -- A Flexible NMT Decoding Platform for Quick Prototyping of New Models and Search Strategies
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Unfolding and Shrinking Neural Machine Translation Ensembles
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The Edit Distance Transducer in Action: The University of Cambridge English-German System at WMT16
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Fast and accurate preordering for SMT using neural networks
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De Gispert, A; Iglesias, G; Byrne, William. - : Association for Computational Linguistics, 2015. : NAACL HLT 2015 - 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference, 2015
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Hierarchical statistical semantic realization for minimal recursion semantics
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Horvat, M; Copestake, Ann; Byrne, William. - : The Association for Computer Linguistics, 2015. : https://aclanthology.org/volumes/W15-01/, 2015. : IWCS 2015 - Proceedings of the 11th International Conference on Computational Semantics, 2015
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The Geometry of Statistical Machine Translation
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Waite, Aurelian; Byrne, William. - : ACL, 2015. : Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2015
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Hispanic-English Database
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Abstract:
*Introduction* Hispanic-English Database contains approximately 30 hours of English and Spanish conversational and read speech with transcripts (24 hours) and metadata collected from 22 non-native English speakers between 1996 and 1998. The corpus was developed by Entropic Research Laboratory, Inc., a developer of speech recognition and speech synthesis software toolkits that was acquired by Microsoft in 1999. Participants were adult native speakers of Spanish as spoken in Central America and South America who resided in the Palo Alto, California area, had lived in the United States for at least one year and demonstrated a basic ability to understand, read and speak English. They read a total of 2200 sentences, 50 each in Spanish and English per speaker. The Spanish sentence prompts were a subset of the materials in LATINO-40 Spanish Read News, and the English sentence prompts were taken from the TIMIT database. Conversations were task-oriented, drawing on exercises similar to those used in English second language instruction and designed to engage the speakers in collaborative, problem-solving activities. *Data* Read speech was recorded on two wideband channels with a Shure SM10A head-mounted microphone in a quiet laboratory environment. The conversational speech was simultaneously recorded on four channels, two of which were used to place phone calls to each subject in two separate offices and to record the incoming speech of the two channels into separate files. The audio was originally saved under the Entropic Audio (ESPS) format using a 16kHz sampling rate and 16 bit samples. Audio files were converted to flac compressed .wav files from the ESPS format. ESPS headers were removed and are presented in this release as *.hdr files that include demographic and technical data. Transcripts were developed with the Entropic Annotator tool and are time-aligned with speaker turns. The transcription conventions were based on those used in the LDC Switchboard and CALLHOME collections. Transcript files are denoted with a .lab extension. Data files and their corresponding label files are stored in subdirectories named using a speaker-pair id and session number. The first three letters identify the speaker on channel A. The last three letters identify the speaker on channel B. Wideband audio files contain *.wb.flac in their file name, and narrow band audio files are denoted with a *.nb.flac in the file name. *Samples* Please view these samples: * Read Speech * Conversational Speech * Transcripts *Updates* None at this time.
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URL: https://catalog.ldc.upenn.edu/LDC2014S05
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