Matches in ScholarlyData for { ?s ?p ?o. }
- 660 creator margot-mieskes.
- 660 creator michael-strube.
- 660 type InProceedings.
- 660 label "Parameters for Topic Boundary Detection in Multi-Party Dialogues".
- 660 sameAs 660.
- 660 abstract "We present a topic boundary detection method that searches for connections between sequences of utterances in multi party dialogues. The connections are established based on word identity. We compare our method to a state-of-the art automatic Topic boundary detection method that was also used on multi party dialogues. We checked various methods of preprocessing of the data, including stemming, lemmatization and stopword filtering with a text-based as well as speech-based stopword lists. Using standard evaluation methods we found that our method outperformed the state-of-the art method.".
- 660 hasAuthorList authorList.
- 660 hasTopic Linguistics.
- 660 isPartOf proceedings.
- 660 keyword "Corpus (creation, annotation, etc.)".
- 660 keyword "Summarisation".
- 660 keyword "Topic detection & tracking".
- 660 title "Parameters for Topic Boundary Detection in Multi-Party Dialogues".
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- item-1 hasContent margot-mieskes.
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- item-2 hasContent michael-strube.
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- 661 creator brigitte-bigi.
- 661 creator eric-castelli.
- 661 creator laurent-besacier.
- 661 creator sethserey-sam.
- 661 creator sopheap-seng.
- 661 type InProceedings.
- 661 label "First Broadcast News Transcription System for Khmer Language".
- 661 sameAs 661.
- 661 abstract "In this paper we present an overview on the development of a large vocabulary continuous speech recognition (LVCSR) system for Khmer, the official language of Cambodia, spoken by more than 15 million people. As an under-resourced language, develop a LVCSR system for Khmer is a challenging task. We describe our methodologies for quick language data collection and processing for language modeling and acoustic modeling. For language modeling, we investigate the use of word and sub-word as basic modeling unit in order to see the potential of sub-word units in the case of unsegmented language like Khmer. Grapheme-based acoustic modeling is used to quickly build our Khmer language acoustic model. Furthermore, the approaches and tools used for the development of our system are documented and made publicly available on the web. We hope this will contribute to accelerate the development of LVCSR system for a new language, especially for under-resource languages of developing countries where resources and expertise are limited.".
- 661 hasAuthorList authorList.
- 661 hasTopic Linguistics.
- 661 isPartOf proceedings.
- 661 keyword "Corpus (creation, annotation, etc.)".
- 661 keyword "Speech recognition and understanding".
- 661 keyword "Tools, systems, applications".
- 661 title "First Broadcast News Transcription System for Khmer Language".
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- item-1 hasContent sopheap-seng.
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- item-2 hasContent sethserey-sam.
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- item-3 hasContent laurent-besacier.
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- item-4 hasContent brigitte-bigi.
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- item-5 hasContent eric-castelli.
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- 662 creator christoph-ringlstetter.
- 662 creator randy-goebel.
- 662 creator weiruo-qu.
- 662 type InProceedings.
- 662 label "Targeting Chinese Nominal Compounds in Corpora".
- 662 sameAs 662.
- 662 abstract "For compounding languages, a great part of the topical semantics is transported via nominal compounds. Various applications of natural language processing can profit from explicit access to these compounds, provided by a lexicon. The best way to acquire such a resource is to harvest corpora that represent the domain in question. For Chinese, a significant difficulty lies in the fact that the text comes as a string of characters, only segmented by sentence boundaries. Extraction algorithms that solely rely on context variety do not perform precisely enough. We propose a pipeline of filters that starts from a candidate set established by accessor variety and then employs several methods to improve precision. For the experiments the Xinhua part of the Chinese Gigaword Corpus was used. We extracted a random sample of 200 story texts with 119,509 Hanzi characters. All compound words of this evaluation corpus were tagged, segmented into their morphemes, and augmented with the POS-information of their segments. A cascade of filters applied to a preliminary set of compound candidates led to a very high precision of over 90%, measured for the types. The result also holds for a small corpus where a solely contextual method introduces too much noise, even for the longer compounds. An introduction of MI into the basic candidacy algorithm led to a much higher recall with still reasonable precision for subsequent manual processing. Especially for the four-character compounds, that in our sample represent over 40% of the target data, the method has sufficient efficacy to support the rapid construction of compound dictionaries from domain corpora.".
- 662 hasAuthorList authorList.
- 662 hasTopic Linguistics.
- 662 isPartOf proceedings.
- 662 keyword "Corpus (creation, annotation, etc.)".
- 662 keyword "MultiWord Expressions & Collocations".
- 662 keyword "Statistical methods".
- 662 title "Targeting Chinese Nominal Compounds in Corpora".
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- item-1 hasContent weiruo-qu.
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- item-2 hasContent christoph-ringlstetter.
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- item-3 hasContent randy-goebel.
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- 663 creator alan-lee.
- 663 creator eva-banik.
- 663 type InProceedings.
- 663 label "A Study of Parentheticals in Discourse Corpora - Implications for NLG Systems".