The Experts below are selected from a list of 288 Experts worldwide ranked by ideXlab platform
Anne Christophe - One of the best experts on this subject based on the ideXlab platform.
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phrasal prosody constrains Syntactic Analysis in toddlers
Cognition, 2017Co-Authors: Alex De Carvalho, Isabelle Dautriche, Isabelle Lin, Anne ChristopheAbstract:This study examined whether phrasal prosody can impact toddlers' Syntactic Analysis. French noun-verb homophones were used to create locally ambiguous test sentences (e.g., using the homophone as a noun: [le bebesouris] [a bien mange] - [the baby mouse] [ate well] or using it as a verb: [le bebe] [sourita sa maman] - [the baby] [smiles to his mother], where brackets indicate prosodic phrase boundaries). Although both sentences start with the same words (le-bebe-/suʁi/), they can be disambiguated by the prosodic boundary that either directly precedes the critical word /suʁi/ when it is a verb, or directly follows it when it is a noun. Across two experiments using an intermodal preferential looking procedure, 28-month-olds (Exp. 1 and 2) and 20-month-olds (Exp. 2) listened to the beginnings of these test sentences while watching two images displayed side-by-side on a TV-screen: one associated with the noun interpretation of the ambiguous word (e.g., a mouse) and the other with the verb interpretation (e.g., a baby smiling). The results show that upon hearing the first words of these sentences, toddlers were able to correctly exploit prosodic information to access the Syntactic structure of sentences, which in turn helped them to determine the Syntactic category of the ambiguous word and to correctly identify its intended meaning: participants switched their eye-gaze toward the correct image based on the prosodic condition in which they heard the ambiguous target word. This provides evidence that during the first steps of language acquisition, toddlers are already able to exploit the prosodic structure of sentences to recover their Syntactic structure and predict the Syntactic category of upcoming words, an ability which would be extremely useful to discover the meaning of novel words.
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preschoolers use phrasal prosody online to constrain Syntactic Analysis
Developmental Science, 2016Co-Authors: Alex De Carvalho, Isabelle Dautriche, Anne ChristopheAbstract:Two experiments were conducted to investigate whether young children are able to take into account phrasal prosody when computing the Syntactic structure of a sentence. Pairs of French noun/verb homophones were selected to create locally ambiguous sentences ([la petite ferme] [est tres jolie] 'the small farm is very nice' vs. [la petite] [ferme la fenetre] 'the little girl closes the window'--brackets indicate prosodic boundaries). Although these sentences start with the same three words, ferme is a noun (farm) in the former but a verb (to close) in the latter case. The only difference between these sentence beginnings is the prosodic structure, that reflects the Syntactic structure (with a prosodic boundary just before the critical word when it is a verb, and just after it when it is a noun). Crucially, all words following the homophone were masked, such that prosodic cues were the only disambiguating information. Children successfully exploited prosodic information to assign the appropriate Syntactic category to the target word, in both an oral completion task (4.5-year-olds, Experiment 1) and in a preferential looking paradigm with an eye-tracker (3.5-year-olds and 4.5-year-olds, Experiment 2). These results show that both groups of children exploit the position of a word within the prosodic structure when computing its Syntactic category. In other words, even younger children of 3.5 years old exploit phrasal prosody online to constrain their Syntactic Analysis. This ability to exploit phrasal prosody to compute Syntactic structure may help children parse sentences containing unknown words, and facilitate the acquisition of word meanings.
Alex De Carvalho - One of the best experts on this subject based on the ideXlab platform.
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phrasal prosody constrains Syntactic Analysis in toddlers
Cognition, 2017Co-Authors: Alex De Carvalho, Isabelle Dautriche, Isabelle Lin, Anne ChristopheAbstract:This study examined whether phrasal prosody can impact toddlers' Syntactic Analysis. French noun-verb homophones were used to create locally ambiguous test sentences (e.g., using the homophone as a noun: [le bebesouris] [a bien mange] - [the baby mouse] [ate well] or using it as a verb: [le bebe] [sourita sa maman] - [the baby] [smiles to his mother], where brackets indicate prosodic phrase boundaries). Although both sentences start with the same words (le-bebe-/suʁi/), they can be disambiguated by the prosodic boundary that either directly precedes the critical word /suʁi/ when it is a verb, or directly follows it when it is a noun. Across two experiments using an intermodal preferential looking procedure, 28-month-olds (Exp. 1 and 2) and 20-month-olds (Exp. 2) listened to the beginnings of these test sentences while watching two images displayed side-by-side on a TV-screen: one associated with the noun interpretation of the ambiguous word (e.g., a mouse) and the other with the verb interpretation (e.g., a baby smiling). The results show that upon hearing the first words of these sentences, toddlers were able to correctly exploit prosodic information to access the Syntactic structure of sentences, which in turn helped them to determine the Syntactic category of the ambiguous word and to correctly identify its intended meaning: participants switched their eye-gaze toward the correct image based on the prosodic condition in which they heard the ambiguous target word. This provides evidence that during the first steps of language acquisition, toddlers are already able to exploit the prosodic structure of sentences to recover their Syntactic structure and predict the Syntactic category of upcoming words, an ability which would be extremely useful to discover the meaning of novel words.
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preschoolers use phrasal prosody online to constrain Syntactic Analysis
Developmental Science, 2016Co-Authors: Alex De Carvalho, Isabelle Dautriche, Anne ChristopheAbstract:Two experiments were conducted to investigate whether young children are able to take into account phrasal prosody when computing the Syntactic structure of a sentence. Pairs of French noun/verb homophones were selected to create locally ambiguous sentences ([la petite ferme] [est tres jolie] 'the small farm is very nice' vs. [la petite] [ferme la fenetre] 'the little girl closes the window'--brackets indicate prosodic boundaries). Although these sentences start with the same three words, ferme is a noun (farm) in the former but a verb (to close) in the latter case. The only difference between these sentence beginnings is the prosodic structure, that reflects the Syntactic structure (with a prosodic boundary just before the critical word when it is a verb, and just after it when it is a noun). Crucially, all words following the homophone were masked, such that prosodic cues were the only disambiguating information. Children successfully exploited prosodic information to assign the appropriate Syntactic category to the target word, in both an oral completion task (4.5-year-olds, Experiment 1) and in a preferential looking paradigm with an eye-tracker (3.5-year-olds and 4.5-year-olds, Experiment 2). These results show that both groups of children exploit the position of a word within the prosodic structure when computing its Syntactic category. In other words, even younger children of 3.5 years old exploit phrasal prosody online to constrain their Syntactic Analysis. This ability to exploit phrasal prosody to compute Syntactic structure may help children parse sentences containing unknown words, and facilitate the acquisition of word meanings.
Isabelle Dautriche - One of the best experts on this subject based on the ideXlab platform.
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phrasal prosody constrains Syntactic Analysis in toddlers
Cognition, 2017Co-Authors: Alex De Carvalho, Isabelle Dautriche, Isabelle Lin, Anne ChristopheAbstract:This study examined whether phrasal prosody can impact toddlers' Syntactic Analysis. French noun-verb homophones were used to create locally ambiguous test sentences (e.g., using the homophone as a noun: [le bebesouris] [a bien mange] - [the baby mouse] [ate well] or using it as a verb: [le bebe] [sourita sa maman] - [the baby] [smiles to his mother], where brackets indicate prosodic phrase boundaries). Although both sentences start with the same words (le-bebe-/suʁi/), they can be disambiguated by the prosodic boundary that either directly precedes the critical word /suʁi/ when it is a verb, or directly follows it when it is a noun. Across two experiments using an intermodal preferential looking procedure, 28-month-olds (Exp. 1 and 2) and 20-month-olds (Exp. 2) listened to the beginnings of these test sentences while watching two images displayed side-by-side on a TV-screen: one associated with the noun interpretation of the ambiguous word (e.g., a mouse) and the other with the verb interpretation (e.g., a baby smiling). The results show that upon hearing the first words of these sentences, toddlers were able to correctly exploit prosodic information to access the Syntactic structure of sentences, which in turn helped them to determine the Syntactic category of the ambiguous word and to correctly identify its intended meaning: participants switched their eye-gaze toward the correct image based on the prosodic condition in which they heard the ambiguous target word. This provides evidence that during the first steps of language acquisition, toddlers are already able to exploit the prosodic structure of sentences to recover their Syntactic structure and predict the Syntactic category of upcoming words, an ability which would be extremely useful to discover the meaning of novel words.
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preschoolers use phrasal prosody online to constrain Syntactic Analysis
Developmental Science, 2016Co-Authors: Alex De Carvalho, Isabelle Dautriche, Anne ChristopheAbstract:Two experiments were conducted to investigate whether young children are able to take into account phrasal prosody when computing the Syntactic structure of a sentence. Pairs of French noun/verb homophones were selected to create locally ambiguous sentences ([la petite ferme] [est tres jolie] 'the small farm is very nice' vs. [la petite] [ferme la fenetre] 'the little girl closes the window'--brackets indicate prosodic boundaries). Although these sentences start with the same three words, ferme is a noun (farm) in the former but a verb (to close) in the latter case. The only difference between these sentence beginnings is the prosodic structure, that reflects the Syntactic structure (with a prosodic boundary just before the critical word when it is a verb, and just after it when it is a noun). Crucially, all words following the homophone were masked, such that prosodic cues were the only disambiguating information. Children successfully exploited prosodic information to assign the appropriate Syntactic category to the target word, in both an oral completion task (4.5-year-olds, Experiment 1) and in a preferential looking paradigm with an eye-tracker (3.5-year-olds and 4.5-year-olds, Experiment 2). These results show that both groups of children exploit the position of a word within the prosodic structure when computing its Syntactic category. In other words, even younger children of 3.5 years old exploit phrasal prosody online to constrain their Syntactic Analysis. This ability to exploit phrasal prosody to compute Syntactic structure may help children parse sentences containing unknown words, and facilitate the acquisition of word meanings.
Dongdong Guo - One of the best experts on this subject based on the ideXlab platform.
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research on knowledge representation and automatic recognition of dynamic words for chinese automatic Syntactic Analysis
IEEE Access, 2020Co-Authors: Dongdong Guo, Weiming Peng, Jihua SongAbstract:There are many temporarily constructed dynamic words in Chinese sentences. Dynamic words are sentence building units that are not included in the general lexicon and are not suitable for further Syntactic Analysis. Automatic recognition and Analysis of dynamic words in sentences play an important role in improving the efficiency and accuracy of Chinese automatic Syntactic Analysis. The existing researches on dynamic words mainly focus on the qualitative description of concepts and categories. There is no overall algorithm design and experimental exploration on automatic recognition of dynamic words. In the practice of automatic Syntactic Analysis, dynamic words are generally segmented, and the components are analyzed according to syntax, while the automatic recognition and Analysis of dynamic words as a whole are ignored. In this study, the dynamic word is separated from Syntactic Analysis as the content of lexical Analysis and recognized and analyzed as a whole. This paper uses the method of knowledge engineering to research and analyze dynamic words for Chinese automatic Syntactic Analysis based on sentence pattern structure, initially designs a knowledge representation method of dynamic words, secondly constructs the dynamic word structural mode knowledge base by annotating the dynamic words in the corpus of a certain scale of international Chinese textbooks, and finally explores the automatic recognition methods of dynamic words based on regular expressions, semantic category combinations and machine learning classification algorithms. The experimental results show that the three algorithms can cover the recognition of all types of dynamic words, and achieve relatively ideal accuracy and recall rate.
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formal schema of diagrammatic chinese Syntactic Analysis
Workshop on Chinese Lexical Semantics, 2015Co-Authors: Weiming Peng, Jihua Song, Zhifang Sui, Dongdong GuoAbstract:This paper reviews the research on diagrammatic Chinese Syntactic Analysis and its Treebank construction which use Sentence Component Analysis (SCA) as the main ideas, puts forward a new formal schema of diagrammatic Chinese Syntactic Analysis based on sentence pattern structure, including diagrammatic style and its XML structure. Syntactic schemes are drawn on the sentence pattern system according to the sequence of “basic sentence pattern, extend sentence pattern, complex sentence pattern and special sentence pattern”, while lexical schemes are drawn on the Diagrammatic Unit which covers idioms/proper nouns, Syntactic words and morphology.
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CLSW - Formal Schema of Diagrammatic Chinese Syntactic Analysis
Lecture Notes in Computer Science, 2015Co-Authors: Weiming Peng, Jihua Song, Zhifang Sui, Dongdong GuoAbstract:This paper reviews the research on diagrammatic Chinese Syntactic Analysis and its Treebank construction which use Sentence Component Analysis (SCA) as the main ideas, puts forward a new formal schema of diagrammatic Chinese Syntactic Analysis based on sentence pattern structure, including diagrammatic style and its XML structure. Syntactic schemes are drawn on the sentence pattern system according to the sequence of “basic sentence pattern, extend sentence pattern, complex sentence pattern and special sentence pattern”, while lexical schemes are drawn on the Diagrammatic Unit which covers idioms/proper nouns, Syntactic words and morphology.
Hyuk-chul Kwon - One of the best experts on this subject based on the ideXlab platform.
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ICTAI - Lyrics-Based Emotion Classification Using Feature Selection by Partial Syntactic Analysis
2011 IEEE 23rd International Conference on Tools with Artificial Intelligence, 2011Co-Authors: Minho Kim, Hyuk-chul KwonAbstract:Songs feel emotionally different to listeners depending on their lyrical contents, even when melodies are similar. Accordingly, when using features related to melody, like tempo, rhythm, tune, and musical note, it is difficult to classify emotions accurately through the existing music emotion classification methods. This paper therefore proposes a method for lyrics-based emotion classification using feature selection by partial Syntactic Analysis. Based on the existing emotion ontology, four kinds of Syntactic Analysis rules were applied to extract emotion features from lyrics. The precision and recall rates of the emotion feature extraction were 73% and 70%, respectively. The extracted emotion features along with the NB, HMM, and SVM machine learning methods were used, showing a maximum accuracy rate of 58.8%.
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ALPIT - Korean Syntactic Analysis Using Dependency Rules and Segmentation
2008 International Conference on Advanced Language Processing and Web Information Technology, 2008Co-Authors: Yong-uk Park, Hyuk-chul KwonAbstract:This paper presents a Korean Syntactic Analysis system. This Syntactic analyzer provides an adequate parsing method using the dependency rules and segmentation. We use dependency grammar for Syntactic Analysis. Dependency grammar is very useful for Korean Syntactic Analysis. But dependency grammar makes many ambiguities in Korean Syntactic Analysis system. We try to disambiguate for Syntactic Analysis system by the many dependency rules and segmentation. Segmentation is made during parsing. If two adjacent morphemes have no Syntactic relations, our Syntactic analyzer makes new segment between these two morphemes, and find out all possible partial parse trees of that segmentation and combine them into complete parse trees. Also we use adjacent-rule and adverb subcategorization to disambiguate of Syntactic Analysis. To eliminate the inadequate parse trees, we use the information of predicate argument.
