Pub Date : 2007-09-01DOI: 10.30019/IJCLCLP.200709.0003
Yi-Hsiang Chao, H. Wang, Ruei-Chuan Chang
In a log-likelihood ratio (LLR)-based speaker verification system, the alternative hypothesis is usually difficult to characterize a priori, since the model should cover the space of all possible impostors. In this paper, we propose a new LLR measure in an attempt to characterize the alternative hypothesis in a more effective and robust way than conventional methods. This LLR measure can be further formulated as a non-linear discriminant classifier and solved by kernel-based techniques, such as the Kernel Fisher Discriminant (KFD) and Support Vector Machine (SVM). The results of experiments on two speaker verification tasks show that the proposed methods outperform classical LLR-based approaches.
{"title":"A Novel Characterization of the Alternative Hypothesis Using Kernel Discriminant Analysis for LLR-Based Speaker Verification","authors":"Yi-Hsiang Chao, H. Wang, Ruei-Chuan Chang","doi":"10.30019/IJCLCLP.200709.0003","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200709.0003","url":null,"abstract":"In a log-likelihood ratio (LLR)-based speaker verification system, the alternative hypothesis is usually difficult to characterize a priori, since the model should cover the space of all possible impostors. In this paper, we propose a new LLR measure in an attempt to characterize the alternative hypothesis in a more effective and robust way than conventional methods. This LLR measure can be further formulated as a non-linear discriminant classifier and solved by kernel-based techniques, such as the Kernel Fisher Discriminant (KFD) and Support Vector Machine (SVM). The results of experiments on two speaker verification tasks show that the proposed methods outperform classical LLR-based approaches.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122354668","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 : 2007-06-01DOI: 10.30019/IJCLCLP.200706.0004
J. Myers
MiniJudge is free online open-source software to help theoretical syntacticians collect and analyze native-speaker acceptability judgments in a way that combines the speed and ease of traditional introspective methods with the power and statistical validity afforded by rigorous experimental protocols. This paper shows why MiniJudge is useful, what it feels like to use it, and how it works.
{"title":"MiniJudge: Software for Small-Scale Experimental Syntax","authors":"J. Myers","doi":"10.30019/IJCLCLP.200706.0004","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200706.0004","url":null,"abstract":"MiniJudge is free online open-source software to help theoretical syntacticians collect and analyze native-speaker acceptability judgments in a way that combines the speed and ease of traditional introspective methods with the power and statistical validity afforded by rigorous experimental protocols. This paper shows why MiniJudge is useful, what it feels like to use it, and how it works.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115423269","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 : 2007-03-01DOI: 10.30019/IJCLCLP.200703.0001
N. Campbell
There has been considerable interest recently in the processing of affect in spoken interactions. This paper presents an analysis of some conversational speech corpus data showing that the four prosodic characteristics, duration, pitch, power, and voicing all vary significantly according to both interlocutor differences and differences in familiarity over a fixed period of time with the same interlocutor.
{"title":"Differences in the Speaking Styles of a Japanese Male According to Interlocutor; Showing the Effects of Affect in Conversational Speech","authors":"N. Campbell","doi":"10.30019/IJCLCLP.200703.0001","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200703.0001","url":null,"abstract":"There has been considerable interest recently in the processing of affect in spoken interactions. This paper presents an analysis of some conversational speech corpus data showing that the four prosodic characteristics, duration, pitch, power, and voicing all vary significantly according to both interlocutor differences and differences in familiarity over a fixed period of time with the same interlocutor.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"43 51","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"113993467","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 : 2007-03-01DOI: 10.30019/IJCLCLP.200703.0005
Chung-Hsien Wu, Ze-Jing Chuang
This paper presents an approach to feature compensation for emotion recognition from speech signals. In this approach, the intonation groups (IGs) of the input speech signals are extracted first. The speech features in each selected intonation group are then extracted. With the assumption of linear mapping between feature spaces in different emotional states, a feature compensation approach is proposed to characterize feature space with better discriminability among emotional states. The compensation vector with respect to each emotional state is estimated using the Minimum Classification Error (MCE) algorithm. For the final emotional state decision, the compensated IG-based feature vectors are used to train the Gaussian Mixture Models (GMMs) and Continuous Support Vector Machine (CSVMs) for each emotional state. For GMMs, the emotional state with the GMM having the maximal likelihood ratio is determined as the final output. For CSVMs, the emotional state is determined according to the probability outputs from the CSVMs. The kernel function in CSVM is experimentally decided as a Radial basis function. A comparison in the experiments shows that the proposed IG-based feature compensation can obtain encouraging performance for emotion recognition.
{"title":"Emotion Recognition from Speech Using IG-Based Feature Compensation","authors":"Chung-Hsien Wu, Ze-Jing Chuang","doi":"10.30019/IJCLCLP.200703.0005","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200703.0005","url":null,"abstract":"This paper presents an approach to feature compensation for emotion recognition from speech signals. In this approach, the intonation groups (IGs) of the input speech signals are extracted first. The speech features in each selected intonation group are then extracted. With the assumption of linear mapping between feature spaces in different emotional states, a feature compensation approach is proposed to characterize feature space with better discriminability among emotional states. The compensation vector with respect to each emotional state is estimated using the Minimum Classification Error (MCE) algorithm. For the final emotional state decision, the compensated IG-based feature vectors are used to train the Gaussian Mixture Models (GMMs) and Continuous Support Vector Machine (CSVMs) for each emotional state. For GMMs, the emotional state with the GMM having the maximal likelihood ratio is determined as the final output. For CSVMs, the emotional state is determined according to the probability outputs from the CSVMs. The kernel function in CSVM is experimentally decided as a Radial basis function. A comparison in the experiments shows that the proposed IG-based feature compensation can obtain encouraging performance for emotion recognition.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2007-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130334551","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 : 2006-12-01DOI: 10.30019/IJCLCLP.200612.0005
Wei Jiang, Yi Guan, Xiaolong Wang
A pragmatic Chinese word segmentation approach is presented in this paper based on mixing language models. Chinese word segmentation is composed of several hard sub-tasks, which usually encounter different difficulties. The authors apply the corresponding language model to solve each special sub-task, so as to take advantage of each model. First, a class-based trigram is adopted in basic word segmentation, which applies the Absolute Discount Smoothing algorithm to overcome data sparseness. The Maximum Entropy Model (ME) is also used to identify Named Entities. Second, the authors propose the application of rough sets and average mutual information, etc. to extract special features. Finally, some features are extended through the combination of the word cluster and the thesaurus. The authors' system participated in the Second International Chinese Word Segmentation Bakeoff, and achieved 96.7 and 97.2 in F-measure in the PKU and MSRA open tests, respectively.
{"title":"A Pragmatic Chinese Word Segmentation Approach Based on Mixing Models","authors":"Wei Jiang, Yi Guan, Xiaolong Wang","doi":"10.30019/IJCLCLP.200612.0005","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200612.0005","url":null,"abstract":"A pragmatic Chinese word segmentation approach is presented in this paper based on mixing language models. Chinese word segmentation is composed of several hard sub-tasks, which usually encounter different difficulties. The authors apply the corresponding language model to solve each special sub-task, so as to take advantage of each model. First, a class-based trigram is adopted in basic word segmentation, which applies the Absolute Discount Smoothing algorithm to overcome data sparseness. The Maximum Entropy Model (ME) is also used to identify Named Entities. Second, the authors propose the application of rough sets and average mutual information, etc. to extract special features. Finally, some features are extended through the combination of the word cluster and the thesaurus. The authors' system participated in the Second International Chinese Word Segmentation Bakeoff, and achieved 96.7 and 97.2 in F-measure in the PKU and MSRA open tests, respectively.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115438707","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 : 2006-09-01DOI: 10.30019/IJCLCLP.200609.0002
Jen-wei Kuo, Shih-Hung Liu, H. Wang, Berlin Chen
This paper presents an empirical study of word error minimization approaches for Mandarin large vocabulary continuous speech recognition (LVCSR). First, the minimum phone error (MPE) criterion, which is one of the most popular discriminative training criteria, is extensively investigated for both acoustic model training and adaptation in a Mandarin LVCSR system. Second, the word error minimization (WEM) criterion, used to rescore N-best word strings, is appropriately modified for a Mandarin LVCSR system. Finally, a series of speech recognition experiments is conducted on the MATBN Mandarin Chinese broadcast news corpus. The experiment results demonstrate that the MPE training approach reduces the character error rate (CER) by 12% for a system initially trained with the maximum likelihood (ML) approach. Meanwhile, for unsupervised acoustic model adaptation, MPE-based linear regression (MPELR) adaptation outperforms conventional maximum likelihood linear regression (MLLR) in terms of CER reduction. When the WEM decoding approach is used for N-best rescoring, a slight performance gain over the conventional maximum a posteriori (MAP) decoding method is also observed.
{"title":"An Empirical Study of Word Error Minimization Approaches for Mandarin Large Vocabulary Continuous Speech Recognition","authors":"Jen-wei Kuo, Shih-Hung Liu, H. Wang, Berlin Chen","doi":"10.30019/IJCLCLP.200609.0002","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200609.0002","url":null,"abstract":"This paper presents an empirical study of word error minimization approaches for Mandarin large vocabulary continuous speech recognition (LVCSR). First, the minimum phone error (MPE) criterion, which is one of the most popular discriminative training criteria, is extensively investigated for both acoustic model training and adaptation in a Mandarin LVCSR system. Second, the word error minimization (WEM) criterion, used to rescore N-best word strings, is appropriately modified for a Mandarin LVCSR system. Finally, a series of speech recognition experiments is conducted on the MATBN Mandarin Chinese broadcast news corpus. The experiment results demonstrate that the MPE training approach reduces the character error rate (CER) by 12% for a system initially trained with the maximum likelihood (ML) approach. Meanwhile, for unsupervised acoustic model adaptation, MPE-based linear regression (MPELR) adaptation outperforms conventional maximum likelihood linear regression (MLLR) in terms of CER reduction. When the WEM decoding approach is used for N-best rescoring, a slight performance gain over the conventional maximum a posteriori (MAP) decoding method is also observed.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"52 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2006-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121729983","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.200512.0009
O. Kwong, Benjamin Ka-Yin T'sou
This paper reports on a synchronous corpus-based study of the everyday usage of a set of Chinese judgement terms. An earlier study on Hong Kong data found that these terms were more polysemous than their English counterparts within the legal domain, and were even more fuzzily used in general news reportage. The current study further compares their usage in general texts from other Chinese speech communities (Beijing, Taiwan, and Singapore) to explore the regional differences in lexicalisation and perception of the relevant legal concepts. Corpus data revealed the distinctiveness of the Singapore data, and that the contrasting frequency distributions of the terms and senses could be a result of the varied focus in reportage or the use of alternative expressions for the same concepts in individual communities. The analysis will contribute to the construction and enrichment of Pan-Chinese lexico-semantic resources, which will be useful for many natural language processing applications, such as machine translation.
{"title":"A Synchronous Corpus-Based Study on the Usage and Perception of Judgement Terms in the Pan-Chinese Context","authors":"O. Kwong, Benjamin Ka-Yin T'sou","doi":"10.30019/IJCLCLP.200512.0009","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200512.0009","url":null,"abstract":"This paper reports on a synchronous corpus-based study of the everyday usage of a set of Chinese judgement terms. An earlier study on Hong Kong data found that these terms were more polysemous than their English counterparts within the legal domain, and were even more fuzzily used in general news reportage. The current study further compares their usage in general texts from other Chinese speech communities (Beijing, Taiwan, and Singapore) to explore the regional differences in lexicalisation and perception of the relevant legal concepts. Corpus data revealed the distinctiveness of the Singapore data, and that the contrasting frequency distributions of the terms and senses could be a result of the varied focus in reportage or the use of alternative expressions for the same concepts in individual communities. The analysis will contribute to the construction and enrichment of Pan-Chinese lexico-semantic resources, which will be useful for many natural language processing applications, such as machine translation.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"1 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":"125142943","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.200512.0003
Shih-Min Li, Su-Chu Lin, Keh-Jiann Chen
In this paper, we propose clear-cut definitions of distinct temporal adverbs and provide descriptive features for each class of temporal adverbs. By measuring time points in temporal axis, we revise and reclassify the temporal adverbs listed in [Lu and Ma 1999] into four classes of semantic roles, namely, time, frequency, duration, and time manner. The descriptive features enable us to distinguish temporal relations and predict logical compatibility between temporal adverbs and aspects.
在本文中，我们对不同的时间副词提出了明确的定义，并给出了每一类时间副词的描述性特征。通过测量时间轴上的时间点，我们将[Lu and Ma 1999]中列出的时间副词修改并重新分类为四类语义角色，即时间、频率、持续时间和时间方式。描述性特征使我们能够区分时间关系，并预测时间副词和方面之间的逻辑兼容性。
{"title":"Feature Representations and Logical Compatibility between Temporal Adverbs and Aspects","authors":"Shih-Min Li, Su-Chu Lin, Keh-Jiann Chen","doi":"10.30019/IJCLCLP.200512.0003","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200512.0003","url":null,"abstract":"In this paper, we propose clear-cut definitions of distinct temporal adverbs and provide descriptive features for each class of temporal adverbs. By measuring time points in temporal axis, we revise and reclassify the temporal adverbs listed in [Lu and Ma 1999] into four classes of semantic roles, namely, time, frequency, duration, and time manner. The descriptive features enable us to distinguish temporal relations and predict logical compatibility between temporal adverbs and aspects.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"53 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":"122541607","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.200512.0002
Meichun Liu, C. Chang
This paper examines the collocational patterns of Mandarin verbs of conversation and proposes that a filler classification scheme than the flat structure of 'frames' [cf. Fillmore and Atkins 1992; Baker et al. 2003] is needed to capture the semantic granularity of verb types. The notion of a 'subframe' is introduced and utilized to explain the syntactic-semantic interdependencies among different groups of verbs in the Conversation Frame. The paper aims to provide detailed linguistic motivations for distinguishing subframes within a frame as a semantic anchor for further defining near-synonym sets.
本文考察了汉语会话动词的搭配模式，提出了一种比“框架”的扁平结构更有效的填充分类方案[cf. Fillmore and Atkins 1992;Baker et al. 2003]需要捕获动词类型的语义粒度。引入了“子框架”的概念，并利用“子框架”来解释会话框架中不同组动词之间的句法语义依存关系。本文旨在提供详细的语言动机来区分框架内的子框架，作为进一步定义近义词集的语义锚。
{"title":"From Frame to Subframe: Collocational Asymmetry in Mandarin Verbs of Conversation","authors":"Meichun Liu, C. Chang","doi":"10.30019/IJCLCLP.200512.0002","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200512.0002","url":null,"abstract":"This paper examines the collocational patterns of Mandarin verbs of conversation and proposes that a filler classification scheme than the flat structure of 'frames' [cf. Fillmore and Atkins 1992; Baker et al. 2003] is needed to capture the semantic granularity of verb types. The notion of a 'subframe' is introduced and utilized to explain the syntactic-semantic interdependencies among different groups of verbs in the Conversation Frame. The paper aims to provide detailed linguistic motivations for distinguishing subframes within a frame as a semantic anchor for further defining near-synonym sets.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"95 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":"127099635","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.200512.0012
Siaw-Fong Chung, K. Ahrens, Chu-Ren Huang
The use of lexical resources in linguistic analysis has expanded rapidly in recent years. However, most lexical resources, such as WordNet or online dictionaries, at this point do not usually indicate figurative meanings, such as conceptual metaphors, as part of a lexical entry. Studies that attempt to establish the relationships between literal and figurative language by detecting the connectivity between WordNet relations usually do not deal with linguistic data directly. However, the present study demonstrates that SUMO definitions can be used to identify the source domains used in conceptual metaphors. This is achieved by identifying the relationships between metaphorical expressions and their corresponding ontological nodes. Such links are important because they show which lexical items are mapped under which concepts. This, in turn, helps specify which lexical items in electronic resources involve conceptual mappings. Looking specifically at the concept of PERSON, this work also establishes connectivity between lexical items which are related to “Organism.” Therefore, the methodology reported herein not only aids the categorizing of lexical items according to their conceptual domains but also can establish links between these items. Such bottom-up and top-down analyses of lexical items may provide a means of representing metaphorical entries in lexical resources.
{"title":"Source Domains as Concept Domains in Metaphorical Expressions","authors":"Siaw-Fong Chung, K. Ahrens, Chu-Ren Huang","doi":"10.30019/IJCLCLP.200512.0012","DOIUrl":"https://doi.org/10.30019/IJCLCLP.200512.0012","url":null,"abstract":"The use of lexical resources in linguistic analysis has expanded rapidly in recent years. However, most lexical resources, such as WordNet or online dictionaries, at this point do not usually indicate figurative meanings, such as conceptual metaphors, as part of a lexical entry. Studies that attempt to establish the relationships between literal and figurative language by detecting the connectivity between WordNet relations usually do not deal with linguistic data directly. However, the present study demonstrates that SUMO definitions can be used to identify the source domains used in conceptual metaphors. This is achieved by identifying the relationships between metaphorical expressions and their corresponding ontological nodes. Such links are important because they show which lexical items are mapped under which concepts. This, in turn, helps specify which lexical items in electronic resources involve conceptual mappings. Looking specifically at the concept of PERSON, this work also establishes connectivity between lexical items which are related to “Organism.” Therefore, the methodology reported herein not only aids the categorizing of lexical items according to their conceptual domains but also can establish links between these items. Such bottom-up and top-down analyses of lexical items may provide a means of representing metaphorical entries in lexical resources.","PeriodicalId":436300,"journal":{"name":"Int. J. Comput. Linguistics Chin. Lang. Process.","volume":"6 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":"128626819","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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