A sense-based lexical knowledgebase is a core foundation for language engineering. Two important criteria must be satisfied when constructing a knowledgebase: linguistic felicity and data cohesion. In this paper, we discuss how data cohesion of the sense information collected using the Sinica Sense Management System (SSMS) can be achieved. SSMS manages both lexical entries and word senses, and has been designed and implemented by the Chinese Wordnet Team at Academia Sinica. SSMS contains all the basic information that can be merged with the future Chinese Wordnet. In addition to senses and meaning facets, SSMS also includes the following information: POS, example sentences, corresponding English synset(s) from Princeton WordNet, and lexical semantic relations, such as synonym/antonym and hypernym/hyponym. Moreover, the overarching structure of the system is managed by using a sense serial number, and an inter-entry structure is established by means of cross-references among synsets and homographs. SSMS is not only a versatile development tool and management system for a sense-based lexical knowledgebase. It can also serve as the database backend for both Chinese Wordnet and any sense-based applications for Chinese language processing.
{"title":"The Sinica Sense Management System: Design and Implementation","authors":"Chu-Ren Huang, Chun-Ling Chen, Cui-Xia Weng, Hsiang-Ping Lee, Yong-Xiang Chen, Keh-Jiann Chen","doi":"10.30019/IJCLCLP.200512.0001","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200512.0001","url":null,"abstract":"A sense-based lexical knowledgebase is a core foundation for language engineering. Two important criteria must be satisfied when constructing a knowledgebase: linguistic felicity and data cohesion. In this paper, we discuss how data cohesion of the sense information collected using the Sinica Sense Management System (SSMS) can be achieved. SSMS manages both lexical entries and word senses, and has been designed and implemented by the Chinese Wordnet Team at Academia Sinica. SSMS contains all the basic information that can be merged with the future Chinese Wordnet. In addition to senses and meaning facets, SSMS also includes the following information: POS, example sentences, corresponding English synset(s) from Princeton WordNet, and lexical semantic relations, such as synonym/antonym and hypernym/hyponym. Moreover, the overarching structure of the system is managed by using a sense serial number, and an inter-entry structure is established by means of cross-references among synsets and homographs. SSMS is not only a versatile development tool and management system for a sense-based lexical knowledgebase. It can also serve as the database backend for both Chinese Wordnet and any sense-based applications for Chinese language processing.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"65 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123301813","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-12-01DOI: 10.30019/IJCLCLP.200512.0005
Hao Chen, Tingting He, D. Ji, Changqin Quan
The research on word sense disambiguation (WSD) has great theoretical and practical significance in many fields of natural language processing (NLP). This paper presents an unsupervised approach to Chinese word sense disambiguation based on Hownet (an electronic Chinese lexical resource). In our approach, contexts that include ambiguous words are converted into vectors by means of a second-order context method, and these context vectors are then clustered by the k-means clustering algorithm. Lastly, the ambiguous words can be disambiguated after a similarity calculation process is completed. Our experiments involved extraction of terms, and an 82.62% average accuracy rate was achieved.
{"title":"An Unsupervised Approach to Chinese Word Sense Disambiguation Based on Hownet","authors":"Hao Chen, Tingting He, D. Ji, Changqin Quan","doi":"10.30019/IJCLCLP.200512.0005","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200512.0005","url":null,"abstract":"The research on word sense disambiguation (WSD) has great theoretical and practical significance in many fields of natural language processing (NLP). This paper presents an unsupervised approach to Chinese word sense disambiguation based on Hownet (an electronic Chinese lexical resource). In our approach, contexts that include ambiguous words are converted into vectors by means of a second-order context method, and these context vectors are then clustered by the k-means clustering algorithm. Lastly, the ambiguous words can be disambiguated after a similarity calculation process is completed. Our experiments involved extraction of terms, and an 82.62% average accuracy rate was achieved.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"456 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115283788","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this paper, a bi-lingual large vocaburary speech recognition experiment based on the idea of modeling pronunciation variations is described. The two languages under study are Mandarin Chinese and Taiwanese (Min-nan). These two languages are basically mutually unintelligible, and they have many words with the same Chinese characters and the same meanings, although they are pronounced differently. Observing the bi-lingual corpus, we found five types of pronunciation variations for Chinese characters. A one-pass, three-layer recognizer was developed that includes a combination of bi-lingual acoustic models, an integrated pronunciation model, and a tree-structure based searching net. The recognizer's performance was evaluated under three different pronunciation models. The results showed that the character error rate with integrated pronunciation models was better than that with pronunciation models, using either the knowledge-based or the data-driven approach. The relative frequency ratio was also used as a measure to choose the best number of pronunciation variations for each Chinese character. Finally, the best character error rates in Mandarin and Taiwanese testing sets were found to be 16.2% and 15.0%, respectively, when the average number of pronunciations for one Chinese character was 3.9.
{"title":"Modeling Pronunciation Variation for Bi-Lingual Mandarin/Taiwanese Speech Recognition","authors":"Dau-Cheng Lyu, Ren-Yuan Lyu, Yuang-Chin Chiang, Chun-Nan Hsu","doi":"10.30019/IJCLCLP.200509.0005","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200509.0005","url":null,"abstract":"In this paper, a bi-lingual large vocaburary speech recognition experiment based on the idea of modeling pronunciation variations is described. The two languages under study are Mandarin Chinese and Taiwanese (Min-nan). These two languages are basically mutually unintelligible, and they have many words with the same Chinese characters and the same meanings, although they are pronounced differently. Observing the bi-lingual corpus, we found five types of pronunciation variations for Chinese characters. A one-pass, three-layer recognizer was developed that includes a combination of bi-lingual acoustic models, an integrated pronunciation model, and a tree-structure based searching net. The recognizer's performance was evaluated under three different pronunciation models. The results showed that the character error rate with integrated pronunciation models was better than that with pronunciation models, using either the knowledge-based or the data-driven approach. The relative frequency ratio was also used as a measure to choose the best number of pronunciation variations for each Chinese character. Finally, the best character error rates in Mandarin and Taiwanese testing sets were found to be 16.2% and 15.0%, respectively, when the average number of pronunciations for one Chinese character was 3.9.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126575768","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-09-01DOI: 10.30019/IJCLCLP.200509.0006
Chooi-Ling Goh, Masayuki Asahara, Yuji Matsumoto
During the process of Chinese word segmentation, two main problems occur: segmentation ambiguities and unknown word occurrences. This paper describes a method to solve the segmentation problem. First, we use a dictionary-based approach to segment the text. We apply the Maximum Matching algorithm to segment the text forwards (FMM) and backwards (BMM). Based on the difference between FMM and BMM, and the context, we apply a classification method based on Support Vector Machines to re-assign the word boundaries. In so doing, we use the output of a dictionary-based approach, and then apply a machine-learning-based approach to solve the segmentation problem. Experimental results show that our model can achieve an F-measure of 99.0 for overall segmentation, given the condition that there are no unknown words in the text, and an F-measure of 95.1 if unknown words exist.
{"title":"Chinese Word Segmentation by Classification of Characters","authors":"Chooi-Ling Goh, Masayuki Asahara, Yuji Matsumoto","doi":"10.30019/IJCLCLP.200509.0006","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200509.0006","url":null,"abstract":"During the process of Chinese word segmentation, two main problems occur: segmentation ambiguities and unknown word occurrences. This paper describes a method to solve the segmentation problem. First, we use a dictionary-based approach to segment the text. We apply the Maximum Matching algorithm to segment the text forwards (FMM) and backwards (BMM). Based on the difference between FMM and BMM, and the context, we apply a classification method based on Support Vector Machines to re-assign the word boundaries. In so doing, we use the output of a dictionary-based approach, and then apply a machine-learning-based approach to solve the segmentation problem. Experimental results show that our model can achieve an F-measure of 99.0 for overall segmentation, given the condition that there are no unknown words in the text, and an F-measure of 95.1 if unknown words exist.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131348834","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-07-01DOI: 10.30019/IJCLCLP.200507.0004
H. Wang, Berlin Chen, Jen-wei Kuo, Shih-Sian Cheng
The MATBN Mandarin Chinese broadcast news corpus contains a total of 198 hours of broadcast news from the Public Television Service Foundation (Taiwan) with corresponding transcripts. The primary purpose of this collection is to provide training and testing data for continuous speech recognition evaluation in the broadcast news domain. In this paper, we briefly introduce. the speech corpus and report on some preliminary statistical analysis and speech recognition evaluation results.
{"title":"MATBN: A Mandarin Chinese Broadcast News Corpus","authors":"H. Wang, Berlin Chen, Jen-wei Kuo, Shih-Sian Cheng","doi":"10.30019/IJCLCLP.200507.0004","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200507.0004","url":null,"abstract":"The MATBN Mandarin Chinese broadcast news corpus contains a total of 198 hours of broadcast news from the Public Television Service Foundation (Taiwan) with corresponding transcripts. The primary purpose of this collection is to provide training and testing data for continuous speech recognition evaluation in the broadcast news domain. In this paper, we briefly introduce. the speech corpus and report on some preliminary statistical analysis and speech recognition evaluation results.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132719191","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-07-01DOI: 10.30019/IJCLCLP.200507.0003
S. Tseng
This paper describes the collection and processing of a pilot speech corpus annotated in dialogue acts. The Mandarin Topic-oriented Conversational Corpus (MTCC) consists of annotated transcripts and sound files of conversations between two familiar persons. Particular features of spoken Mandarin, such as discourse particles and paralinguistic sounds, are taken into account in the orthographical transcription. In addition, the dialogue structure is annotated using an annotation scheme developed for topic-specific conversations. Using the annotated materials, we present the results of a preliminary analysis of dialogue structure and dialogue acts. Related transcription tools and web query applications are also introduced in this paper.
{"title":"Mandarin Topic-oriented Conversations","authors":"S. Tseng","doi":"10.30019/IJCLCLP.200507.0003","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200507.0003","url":null,"abstract":"This paper describes the collection and processing of a pilot speech corpus annotated in dialogue acts. The Mandarin Topic-oriented Conversational Corpus (MTCC) consists of annotated transcripts and sound files of conversations between two familiar persons. Particular features of spoken Mandarin, such as discourse particles and paralinguistic sounds, are taken into account in the orthographical transcription. In addition, the dialogue structure is annotated using an annotation scheme developed for topic-specific conversations. Using the annotated materials, we present the results of a preliminary analysis of dialogue structure and dialogue acts. Related transcription tools and web query applications are also introduced in this paper.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116159810","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-07-01DOI: 10.30019/IJCLCLP.200507.0002
Elizabeth Zeitoun, Ching-Hua Yu
In this paper, we deal with the linguistic analysis approach adopted in the Formosan Language Corpora, one of the three main information databases included in the Formosan Language Archive, and the language processing programs that have been built upon it. We first discuss problems related to the transcription of different language corpora. We then deal with annotation rules and standards. We go on to explain the linguistic identification of clauses, sentences and paragraphs, and the computer programs used to obtain an alignment of words, glosses and sentences in Chinese and English. We finally show how we try to cope with analytic inconsistencies through programming. This paper is a complement to Zeitoun et al. [2003] in which we provided an overview of the whole architecture of the Formosan Language Archive.
{"title":"The Formosan Language Archive: Linguistic Analysis and Language Processing","authors":"Elizabeth Zeitoun, Ching-Hua Yu","doi":"10.30019/IJCLCLP.200507.0002","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200507.0002","url":null,"abstract":"In this paper, we deal with the linguistic analysis approach adopted in the Formosan Language Corpora, one of the three main information databases included in the Formosan Language Archive, and the language processing programs that have been built upon it. We first discuss problems related to the transcription of different language corpora. We then deal with annotation rules and standards. We go on to explain the linguistic identification of clauses, sentences and paragraphs, and the computer programs used to obtain an alignment of words, glosses and sentences in Chinese and English. We finally show how we try to cope with analytic inconsistencies through programming. This paper is a complement to Zeitoun et al. [2003] in which we provided an overview of the whole architecture of the Formosan Language Archive.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115300526","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper describes a project that aims to create a Mandarin speech database for the automobile setting (TAICAR). A group of researchers from several universities and research institutes in Taiwan have participated in the project. The goal is to generate a corpus for the development and testing of various speech-processing techniques. There are six recording sites in this project. Various words, sentences, and spontaneously queries uttered in the vehicular navigation setting have been collected in this project. A preliminary corpus of utterances from 192 speakers was created from utterances generated in different vehicles. The database contains more than 163,000 files, occupying 16.8 gigabytes of disk space.
{"title":"TAICAR-The Collection and Annotation of an In-Car Speech Database Created in Taiwan","authors":"Hsien-Chang Wang, Chung-Hsien Yang, Jhing-Fa Wang, Chung-Hsien Wu, Jen-Tzung Chien","doi":"10.30019/IJCLCLP.200507.0005","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200507.0005","url":null,"abstract":"This paper describes a project that aims to create a Mandarin speech database for the automobile setting (TAICAR). A group of researchers from several universities and research institutes in Taiwan have participated in the project. The goal is to generate a corpus for the development and testing of various speech-processing techniques. There are six recording sites in this project. Various words, sentences, and spontaneously queries uttered in the vehicular navigation setting have been collected in this project. A preliminary corpus of utterances from 192 speakers was created from utterances generated in different vehicles. The database contains more than 163,000 files, occupying 16.8 gigabytes of disk space.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132861929","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-06-01DOI: 10.30019/IJCLCLP.200507.0001
Chengyuan Lin, J. Jang, Kuan-Ting Chen
Precise phone/syllable boundary labeling of the utterances in a speech corpus plays an important role in constructing a corpus-based TTS (text-to-speech) system. However, automatic labeling based on Viterbi forced alignment does not always produce satisfactory results. Moreover, a suitable labeling method for one language does not necessarily produce desirable results for another language. Hence in this paper, we propose a new procedure for refining the boundaries of utterances in a Mandarin speech corpus. This procedure employs different sets of acoustic features for four different phonetic categories. In addition, a new scheme is proposed to deal with the ”periodic voiced + periodic voiced” case, which produced most of the segmentation errors in our experiment. Several experiments were conducted to demonstrate the feasibility of the proposed approach.
{"title":"Automatic Segmentation and Labeling for Mandarin Chinese Speech Corpora for Concatenation-based TTS","authors":"Chengyuan Lin, J. Jang, Kuan-Ting Chen","doi":"10.30019/IJCLCLP.200507.0001","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200507.0001","url":null,"abstract":"Precise phone/syllable boundary labeling of the utterances in a speech corpus plays an important role in constructing a corpus-based TTS (text-to-speech) system. However, automatic labeling based on Viterbi forced alignment does not always produce satisfactory results. Moreover, a suitable labeling method for one language does not necessarily produce desirable results for another language. Hence in this paper, we propose a new procedure for refining the boundaries of utterances in a Mandarin speech corpus. This procedure employs different sets of acoustic features for four different phonetic categories. In addition, a new scheme is proposed to deal with the ”periodic voiced + periodic voiced” case, which produced most of the segmentation errors in our experiment. Several experiments were conducted to demonstrate the feasibility of the proposed approach.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132029058","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2005-03-01DOI: 10.30019/IJCLCLP.200503.0005
Thomas C. Chuang, K. Yeh
We present a new approach to aligning sentences in bilingual parallel corpora based on punctuation, especially for English and Chinese. Although the length-based approach produces high accuracy rates of sentence alignment for clean parallel corpora written in two Western languages, such as French-English or German-English, it does not work as well for parallel corpora that are noisy or written in two disparate languages such as Chinese-English. It is possible to use cognates on top of the length-based approach to increase the alignment accuracy. However, cognates do not exist between two disparate languages, which limit the applicability of the cognate-based approach. In this paper, we examine the feasibility of exploiting the statistically ordered matching of punctuation marks in two languages to achieve high accuracy sentence alignment. We have experimented with an implementation of the proposed method on parallel corpora, the Chinese-English Sinorama Magazine Corpus and Scientific American Magazine articles, with satisfactory results. Compared with the length-based method, the proposed method exhibits better precision rates based on our experimental reuslts. Highly promising improvement was observed when both the punctuation-based and length-based methods were adopted within a common statistical framework. We also demonstrate that the method can be applied to other language pairs, such as English-Japanese, with minimal additional effort.
{"title":"Aligning Parallel Bilingual Corpora Statistically with Punctuation Criteria","authors":"Thomas C. Chuang, K. Yeh","doi":"10.30019/IJCLCLP.200503.0005","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200503.0005","url":null,"abstract":"We present a new approach to aligning sentences in bilingual parallel corpora based on punctuation, especially for English and Chinese. Although the length-based approach produces high accuracy rates of sentence alignment for clean parallel corpora written in two Western languages, such as French-English or German-English, it does not work as well for parallel corpora that are noisy or written in two disparate languages such as Chinese-English. It is possible to use cognates on top of the length-based approach to increase the alignment accuracy. However, cognates do not exist between two disparate languages, which limit the applicability of the cognate-based approach. In this paper, we examine the feasibility of exploiting the statistically ordered matching of punctuation marks in two languages to achieve high accuracy sentence alignment. We have experimented with an implementation of the proposed method on parallel corpora, the Chinese-English Sinorama Magazine Corpus and Scientific American Magazine articles, with satisfactory results. Compared with the length-based method, the proposed method exhibits better precision rates based on our experimental reuslts. Highly promising improvement was observed when both the punctuation-based and length-based methods were adopted within a common statistical framework. We also demonstrate that the method can be applied to other language pairs, such as English-Japanese, with minimal additional effort.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2005-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129768952","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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