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Neural MT and Human Post-editing : a Method to Improve Editorial Quality
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In: ISSN: 1134-8941 ; Interlingüística ; https://halshs.archives-ouvertes.fr/halshs-03603590 ; Interlingüística, Alacant [Spain] : Universitat Autònoma de Barcelona, 2022, pp.15-36 (2022)
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Human evaluation of three machine translation systems : from quality to attitudes by professional translators
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Quantitative Fine-grained Human Evaluation of Machine Translation Systems: a Case Study on English to Croatian
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In: Articles (2018)
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Human-Guided Evolutionary-Based Linguistics Approach For Automatic Story Generation ...
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MSEE: Stochastic Cognitive Linguistic Behavior Models for Semantic Sensing
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In: DTIC (2013)
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English → Russian MT evaluation campaign
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In: ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (2013)
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Human-Guided Evolutionary-Based Linguistics Approach For Automatic Story Generation
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Bucking the Trend: Large-Scale Cost-Focused Active Learning for Statistical Machine Translation
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Task muddiness, intelligence metrics, and the necessity of autonomous mental development
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In: http://www.cse.msu.edu/~cse841/papers/MuddyTasks.pdf (2009)
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A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping ...
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A Method for Stopping Active Learning Based on Stabilizing Predictions and the Need for User-Adjustable Stopping
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Automating Convoy Training Assessment to Improve Soldier Performance
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In: DTIC (2008)
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Differential Effect of Correct Name Translation on Human and Automated Judgments of Translation Acceptability: A Pilot Study
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In: DTIC (2008)
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Automatic Computation of . . .
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In: http://www.informatik.uni-freiburg.de/~ksimon/papers/CIKM-06-Proximity.pdf (2006)
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Toward Joint Segmentation and Classification of Dialog Acts in Multiparty Meetings
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In: DTIC (2005)
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Abstract:
The authors present baseline results for the joint segmentation and classification of dialog acts (DAs) of the International Computer Science Institute (ICSI) Meeting Corpus. Two simple approaches based on word information are investigated and compared with previous work on the same task. The first approach is based on a Hidden-Event Language Model (HE-LM), and the second relies on a Hidden Markov Model (HMM) based tagger. The HE-LM is frequently used for detection of sentence boundaries where after each word the model predicts a nonboundary or a sentence boundary event. In contrast, the authors use the HE-LM to predict not only a DA boundary or a nonboundary event, but the type of the DA boundary at the same time. The second technique relies on the concept of disambiguation of words, which is widely used in the form of HMM-based Part of Speech (POS) taggers. The authors also describe several metrics to assess the quality of the segmentation alone and the joint performance of segmentation and classification: NIST-SU, Lenient, Strict, DA Error Rate (DER), and DSER(DA Segmented Error Rate). As the investigated methods do not take into account prosodic features, it comes as no surprise that the overall performance of these systems is not always as good as previous work. Based on the experiments, the authors suggest that the lenient metric should not be used alone but in combination with other metrics that take into account the quality of the segmentation as well. The results provided in this paper serve as a baseline against which the authors will measure the results of future work on joint segmentation and classification. ; Prepared in cooperation with SRI International. The original document contains color images.
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Keyword:
*AUTOMATION; *CLASSIFICATION; *DIALOG ACTS; *JOINT SEGMENTATION; *SEGMENTED; *SPEECH ANALYSIS; *SPEECH COMMUNICATION; *VOICE COMMUNICATIONS; *WORDS(LANGUAGE); BOUNDARIES; DER(DA ERROR RATE); DETECTION; DSER(DA SEGMENTATION ERROR RATE); DYNAMIC PROGRAMMING; ERRORS; HE-LM(HIDDEN-EVENT LANGUAGE MODEL); HMM(HIDDEN MARKOV MODEL); HUMAN COMMUNICATION; HUMAN SPEECH; Information Science; Linguistics; MARKOV PROCESSES; MULTIPARTY MEETINGS; NATURAL LANGUAGE; PERFORMANCE METRICS; SOCIAL COMMUNICATION; SPEECH SEGMENTATION
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA444859 http://www.dtic.mil/docs/citations/ADA444859
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Symposium on Speech Communication Metrics and Human Performance.
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In: DTIC AND NTIS (1995)
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Structural analysis of hypertexts: Identifying hierarchies and useful metrics
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In: http://www.cs.technion.ac.il/~ehudr/publications/pdf/BotafogoRS92a.pdf (1992)
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Natural Language Processing Systems Evaluation Workshop Held in Berkely, California on 18 June 1991
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In: DTIC AND NTIS (1991)
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Metrics for MT evaluation: Evaluating reordering
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In: http://homepages.inf.ed.ac.uk/miles/papers/mt09.pdf
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