[PDF] Top 20 Proceedings of the 27th Conference on Computational Linguistics and Speech Processing (ROCLING 2015)
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Proceedings of the 27th Conference on Computational Linguistics and Speech Processing (ROCLING 2015)
... ROCLING 2015 features two distinguished lectures from the renowned speakers in speech processing as well as natural language ...“Data Processing and Information Extraction for Social ... See full document
14
Proceedings of the 23rd Conference on Computational Linguistics and Speech Processing (ROCLING 2011)
... 傳統語言模型 (Language Models) 是藉由使用大量的文字語料訓練而成，以機 率模型來描述自然語言的規律性。N 連 ( N -gram) 語言模型是最常見的語言模 型，被用來估測每一個詞出現在已知前N -1 個歷史詞之後的條件機率。此外， 傳統語言模型大多是以最大化相似度為訓練目標；因此，當它被使用於語音 辨識上時，對於降低語音辨識錯誤率常會有所侷限。近年來，有別於傳統語 言模型的鑑別式語言模型 ... See full document
15
Proceedings of the 24th Conference on Computational Linguistics and Speech Processing (ROCLING 2012)
... 24th Conference on Computational Linguistics and Speech Processing at Yuan Ze ...for Computational Linguistics and Chinese Language Processing (ACLCLP), ... See full document
14
Proceedings of the 27th International Conference on Computational Linguistics: Tutorial Abstracts
... Asli Celikyilmaz is currently a researcher at the Deep Learning Technology Center at Microsfot Re- search. Previously, she was a Research Scientist at Microsoft Bing from 2010 until 2016 focusing on deep learning models ... See full document
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Proceedings of the 25th Conference on Computational Linguistics and Speech Processing (ROCLING 2013)
... of speech variation and any condition of the speech data available for training and ...effective speech databases covering a wide range of variations, active learning for automatically selecting data ... See full document
12
Proceedings of the 20th Nordic Conference of Computational Linguistics (NODALIDA 2015)
... It is well-known that natural language has built-in redundancy. By using context, we can often guess the next word or character in a text. Two practical communi- ties have independently exploited this fact. First, ... See full document
28
Proceedings of the 22nd International Conference on Computational Linguistics (Coling 2008)
... on speech technologies, in our opinion even less than in earlier COLING ...known speech conferences. This year’s ACL conference also had just a single speech processing ... See full document
18
Proceedings of the 29th Conference on Computational Linguistics and Speech Processing (ROCLING 2017)
... in speech coding, speech synthesis, speech recognition and signal processing for the development of the DSC-2000 Voice ...information processing, speech and speaker recognition, ... See full document
11
Proceedings of the 30th Conference on Computational Linguistics and Speech Processing (ROCLING 2018)
... 30th Conference on Computational Linguistics and Speech Processing (ROCLING), the flagship conference on computational linguistics, natural language ... See full document
12
Proceedings of the 28th Conference on Computational Linguistics and Speech Processing (ROCLING 2016)
... language processing (NLP) is often viewed as a hard problem and all people either researchers or users often feel frustrated by the limitations and mistakes of a NLP ... See full document
15
Proceedings of the 26th Conference on Computational Linguistics and Speech Processing (ROCLING 2014)
... ... See full document
14
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Tutorial Abstracts
... We had 20 thematic areas and each area was chaired by two or more area chairs. Thanks to over 800 responsive reviewers, the review process proceeded in a very smooth manner, and each paper was read at least by three ... See full document
10
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Tutorial Abstracts
... To effectively cover the broad spectrum of topics included in the conference, we have 18 thematic areas, each chaired by two or more area chairs. We are extremely grateful to the area chairs, who led and monitored ... See full document
12
Practical Very Large Scale CRFs
... Conditional Random Fields (CRFs) are a widely-used approach for supervised sequence labelling, notably due to their ability to handle large description spaces and to integrate structural dependency be- tween labels. Even ... See full document
10
Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers
... COLING has changed over the years, together with the changes in our field. But it has always been important for ICCL to maintain the COLING “spirit”: we always wanted COLING to be an inclusive and broad ... See full document
80
T Know: a Knowledge Graph based Question Answering and Infor mation Retrieval System for Traditional Chinese Medicine
... T-Know is a knowledge service system based on the constructed knowledge graph of Tradi- tional Chinese Medicine (TCM). Using authorized and anonymized clinical records, medicine clinical guidelines, teaching materials, ... See full document
5
A Flexible and Easy to use Semantic Role Labeling Framework for Different Languages
... During the first decade of the 21 st century, mapping from the syntactic analysis of a sentence to its se- mantic representation has received a central interest in the natural language processing (NLP) community. ... See full document
5
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: Technical Papers
... We had 20 thematic areas and each area was chaired by two or more area chairs. Thanks to over 800 responsive reviewers, the review process proceeded in a very smooth manner, and each paper was read at least by three ... See full document
50
Proceedings of COLING 2014, the 25th International Conference on Computational Linguistics: System Demonstrations
... The demonstration session complements the conference’s presentation and poster sessions and is focused on working software systems that are the tangible outcomes of research on computational linguistics. As ... See full document
12
Simulating Language Evolution: a Tool for Historical Linguistics
... We use lemmas (dictionary word forms) as input. We further experiment with some additional pre- processing steps on the input data (diacritics removal and stemming). The results are slightly improved when ... See full document
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