The measurement of meaning

Child psychiatrists, pediatricians, and other child clinicians need to have a solid understanding of child language development. There are at least four important reasons that make this necessary. First, slowing, arrest, and deviation of language development are highly associated with, and complicate the course of, child psychopathology. Second, language competence plays a crucial role in emotional and mood regulation, evaluation, and therapy. Third, language deficits are the most frequent underpinning of the learning disorders, ubiquitous in our clinical populations. Fourth, clinicians should not confuse the rich linguistic and dialectal diversity of our clinical populations with abnormalities in child language development. The challenge for the clinician becomes, then, how to get immersed in the captivating field of child language acquisition without getting overwhelmed by its conceptual and empirical complexity. In the past 50 years and since the seminal works of Roger Brown, Jerome Bruner, and Catherine Snow, child language researchers (often known as developmental psycholinguists) have produced a remarkable body of knowledge. Linguists such as Chomsky and philosophers such as Grice have strongly influenced the science of child language. One of the major tenets of Chomskian linguistics (known as generative grammar) is that children’s capacity to acquire language is “hardwired” with “universal grammar”—an innate language acquisition device (LAD), a language “instinct”—at its core. This view is in part supported by the assertion that the linguistic input that children receive is relatively dismal and of poor quality relative to the high quantity and quality of output that they manage to produce after age 2 and that only an advanced, innate capacity to decode and organize linguistic input can enable them to “get from here (prelinguistic infant) to there (linguistic child).” In “Constructing a Language,” Tomasello presents a contrasting theory of how the child acquires language: It is not a universal grammar that allows for language development. Rather, human cognition universals of communicative needs and vocal-auditory processing result in some language universals, such as nouns and verbs as expressions of reference and predication (p. 19). The author proposes that two sets of cognitive skills resulting from biological/phylogenetic adaptations are fundamental to the ontogenetic origins of language. These sets of inherited cognitive skills are intentionreading on the one hand and pattern-finding, on the other. Intention-reading skills encompass the prelinguistic infant’s capacities to share attention to outside events with other persons, establishing joint attentional frames, to understand other people’s communicative intentions, and to imitate the adult’s communicative intentions (an intersubjective form of imitation that requires symbolic understanding and perspective-taking). Pattern-finding skills include the ability of infants as young as 7 months old to analyze concepts and percepts (most relevant here, auditory or speech percepts) and create concrete or abstract categories that contain analogous items. Tomasello, a most prominent developmental scientist with research foci on child language acquisition and on social cognition and social learning in children and primates, succinctly and clearly introduces the major points of his theory and his views on the origins of language in the initial chapters. In subsequent chapters, he delves into the details by covering most language acquisition domains, namely, word (lexical) learning, syntax, and morphology and conversation, narrative, and extended discourse. Although one of the remaining domains (pragmatics) is at the core of his theory and permeates the text throughout, the relative paucity of passages explicitly devoted to discussing acquisition and proBOOK REVIEWS

Constructing a language: A usage-based theory of language acquisition

Information about the affective meanings of words is used by researchers working on emotions and moods, word recognition and memory, and text-based sentiment analysis. Three components of emotions are traditionally distinguished: valence (the pleasantness of a stimulus), arousal (the intensity of emotion provoked by a stimulus), and dominance (the degree of control exerted by a stimulus). Thus far, nearly all research has been based on the ANEW norms collected by Bradley and Lang (1999) for 1,034 words. We extended that database to nearly 14,000 English lemmas, providing researchers with a much richer source of information, including gender, age, and educational differences in emotion norms. As an example of the new possibilities, we included stimuli from nearly all of the category norms (e.g., types of diseases, occupations, and taboo words) collected by Van Overschelde, Rawson, and Dunlosky (Journal of Memory and Language 50:289-335, 2004), making it possible to include affect in studies of semantic memory.

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Norms of valence, arousal, and dominance for 13,915 English lemmas

The quarterly journal of experimental psychology

What Happened in CLEF 2004?.- What Happened in CLEF 2004?.- I. Ad Hoc Text Retrieval Tracks.- CLEF 2004: Ad Hoc Track Overview and Results Analysis.- Selection and Merging Strategies for Multilingual Information Retrieval.- Using Surface-Syntactic Parser and Deviation from Randomness.- Cross-Language Retrieval Using HAIRCUT at CLEF 2004.- Experiments on Statistical Approaches to Compensate for Limited Linguistic Resources.- Application of Variable Length N-Gram Vectors to Monolingual and Bilingual Information Retrieval.- Integrating New Languages in a Multilingual Search System Based on a Deep Linguistic Analysis.- IR-n r2: Using Normalized Passages.- Using COTS Search Engines and Custom Query Strategies at CLEF.- Report on Thomson Legal and Regulatory Experiments at CLEF-2004.- Effective Translation, Tokenization and Combination for Cross-Lingual Retrieval.- Two-Stage Refinement of Transitive Query Translation with English Disambiguation for Cross-Language Information Retrieval: An Experiment at CLEF 2004.- Dictionary-Based Amharic - English Information Retrieval.- Dynamic Lexica for Query Translation.- SINAI at CLEF 2004: Using Machine Translation Resources with a Mixed 2-Step RSV Merging Algorithm.- Mono- and Crosslingual Retrieval Experiments at the University of Hildesheim.- University of Chicago at CLEF2004: Cross-Language Text and Spoken Document Retrieval.- UB at CLEF2004: Cross Language Information Retrieval Using Statistical Language Models.- MIRACLE's Hybrid Approach to Bilingual and Monolingual Information Retrieval.- Searching a Russian Document Collection Using English, Chinese and Japanese Queries.- Dublin City University at CLEF 2004: Experiments in Monolingual, Bilingual and Multilingual Retrieval.- Finnish, Portuguese and Russian Retrieval with Hummingbird SearchServerTM at CLEF 2004.- Data Fusion for Effective European Monolingual Information Retrieval.- The XLDB Group at CLEF 2004.- The University of Glasgow at CLEF 2004: French Monolingual Information Retrieval with Terrier.- II. Domain-Specific Document Retrieval.- The Domain-Specific Track in CLEF 2004: Overview of the Results and Remarks on the Assessment Process.- University of Hagen at CLEF 2004: Indexing and Translating Concepts for the GIRT Task.- IRIT at CLEF 2004: The English GIRT Task.- Ricoh at CLEF 2004.- GIRT and the Use of Subject Metadata for Retrieval.- III. Interactive Cross-Language Information Retrieval.- iCLEF 2004 Track Overview: Pilot Experiments in Interactive Cross-Language Question Answering.- Interactive Cross-Language Question Answering: Searching Passages Versus Searching Documents.- Improving Interaction with the User in Cross-Language Question Answering Through Relevant Domains and Syntactic Semantic Patterns.- Cooperation, Bookmarking, and Thesaurus in Interactive Bilingual Question Answering.- Summarization Design for Interactive Cross-Language Question Answering.- Interactive and Bilingual Question Answering Using Term Suggestion and Passage Retrieval.- IV. Multiple Language Question Answering.- Overview of the CLEF 2004 Multilingual Question Answering Track.- A Question Answering System for French.- Cross-Language French-English Question Answering Using the DLT System at CLEF 2004.- Experiments on Robust NL Question Interpretation and Multi-layered Document Annotation for a Cross-Language Question/Answering System.- Making Stone Soup: Evaluating a Recall-Oriented Multi-stream Question Answering System for Dutch.- The DIOGENE Question Answering System at CLEF-2004.- Cross-Lingual Question Answering Using Off-the-Shelf Machine Translation.- Bulgarian-English Question Answering: Adaptation of Language Resources.- Answering French Questions in English by Exploiting Results from Several Sources of Information.- Finnish as Source Language in Bilingual Question Answering.- miraQA: Experiments with Learning Answer Context Patterns from the Web.- Question Answering for Spanish Supported by Lexical Context Annotation.- Question Answering Using Sentence Parsing and Semantic Network Matching.- First Evaluation of Esfinge - A Question Answering System for Portuguese.- University of Evora in QA@CLEF-2004.- COLE Experiments at QA@CLEF 2004 Spanish Monolingual Track.- Does English Help Question Answering in Spanish?.- The TALP-QA System for Spanish at CLEF 2004: Structural and Hierarchical Relaxing of Semantic Constraints.- ILC-UniPI Italian QA.- Question Answering Pilot Task at CLEF 2004.- Evaluation of Complex Temporal Questions in CLEF-QA.- V. Cross-Language Retrieval in Image Collections.- The CLEF 2004 Cross-Language Image Retrieval Track.- Caption and Query Translation for Cross-Language Image Retrieval.- Pattern-Based Image Retrieval with Constraints and Preferences on ImageCLEF 2004.- How to Visually Retrieve Images from the St. Andrews Collection Using GIFT.- UNED at ImageCLEF 2004: Detecting Named Entities and Noun Phrases for Automatic Query Expansion and Structuring.- Dublin City University at CLEF 2004: Experiments with the ImageCLEF St. Andrew's Collection.- From Text to Image: Generating Visual Query for Image Retrieval.- Toward Cross-Language and Cross-Media Image Retrieval.- FIRE - Flexible Image Retrieval Engine: ImageCLEF 2004 Evaluation.- MIRACLE Approach to ImageCLEF 2004: Merging Textual and Content-Based Image Retrieval.- Cross-Media Feedback Strategies: Merging Text and Image Information to Improve Image Retrieval.- ImageCLEF 2004: Combining Image and Multi-lingual Search for Medical Image Retrieval.- Multi-modal Information Retrieval Using FINT.- Medical Image Retrieval Using Texture, Locality and Colour.- SMIRE: Similar Medical Image Retrieval Engine.- A Probabilistic Approach to Medical Image Retrieval.- UB at CLEF2004 Cross Language Medical Image Retrieval.- Content-Based Queries on the CasImage Database Within the IRMA Framework.- Comparison and Combination of Textual and Visual Features for Interactive Cross-Language Image Retrieval.- MSU at ImageCLEF: Cross Language and Interactive Image Retrieval.- VI. Cross-Language Spoken Document Retrieval.- CLEF 2004 Cross-Language Spoken Document Retrieval Track.- VII. Issues in CLIR and in Evaluation.- The Key to the First CLEF with Portuguese: Topics, Questions and Answers in CHAVE.- How Do Named Entities Contribute to Retrieval Effectiveness?.

Multilingual information access for text, speech and images : 5th workshop of the cross-language evaluation forum, CLEF 2004, Bath, UK, September 15-17, 2004, revised selected papers

This study presents the adaptation of the Affective Norms for English Words (ANEW; Bradley & Lang, 1999a) for European Portuguese (EP). The EP adaptation of the ANEW was based on the affective ratings made by 958 college students who were EP native speakers. Subjects assessed about 60 words by considering the affective dimensions of valence, arousal, and dominance, using the Self-Assessment Manikin (SAM) in either a paper-and-pencil or a Web survey procedure. Results of the adaptation of the ANEW for EP are presented. Furthermore, the differences between EP, American (Bradley & Lang, 1999a), and Spanish (Redondo, Fraga, Padron, & Comesana, Behavior Research Methods, 39, 600–605, 2007) standardizations were explored. Results showed that the ANEW words were understood in a similar way by EP, American, and Spanish subjects, although some sex and cross-cultural differences were observed. The EP adaptation of the ANEW is shown to be a valid and useful tool that will allow researchers to control and/or manipulate the affective properties of stimuli, as well as to develop cross-linguistic studies. The normative values of EP adaptation of the ANEW can be downloaded at http://brm.psychonomic-journals.org/content/supplemental.

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The adaptation of the Affective Norms for English Words (ANEW) for European Portuguese

This document presents the TerminUM project and the work done in its statistical word aligner workbench (NATools). It shows a variety of alignment methods for parallel corpora and discusses the resulting terminological dictionaries and their use: evaluation of sentence translations; construction of a multi-level navigation system for linguistic studies or statistical translations

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NATools, a statistical word aligner workbench

We examined the potential advantage of the lexical databases using subtitles and present SUBTLEX-PT, a new lexical database for 132,710 Portuguese words obtained from a 78 million corpus based on f...

On the advantages of word frequency and contextual diversity measures extracted from subtitles: The case of Portuguese.

https://repositorium.sdum.uminho.pt/bitstream/1822/638/1/jspell.pm.pdf

jspell.pm: um módulo de análise morfológica para uso em processamento de linguagem natural

In this article, we present Procura-PALavras (P-PAL), a Web-based interface for a new European Portuguese (EP) lexical database. Based on a contemporary printed corpus of over 227 million words, P-PAL provides a broad range of word attributes and statistics, including several measures of word frequency (e.g., raw counts, per-million word frequency, logarithmic Zipf scale), morpho-syntactic information (e.g., parts of speech [PoSs], grammatical gender and number, dominant PoS, and frequency and relative frequency of the dominant PoS), as well as several lexical and sublexical orthographic (e.g., number of letters; consonant–vowel orthographic structure; density and frequency of orthographic neighbors; orthographic Levenshtein distance; orthographic uniqueness point; orthographic syllabification; and trigram, bigram, and letter type and token frequencies), and phonological measures (e.g., pronunciation, number of phonemes, stress, density and frequency of phonological neighbors, transposed and phonographic neighbors, syllabification, and biphone and phone type and token frequencies) for ~53,000 lemmatized and ~208,000 nonlemmatized EP word forms. To obtain these metrics, researchers can choose between two word queries in the application: (i) analyze words previously selected for specific attributes and/or lexical and sublexical characteristics, or (ii) generate word lists that meet word requirements defined by the user in the menu of analyses. For the measures it provides and the flexibility it allows, P-PAL will be a key resource to support research in all cognitive areas that use EP verbal stimuli. P-PAL is freely available at http://p-pal.di.uminho.pt/tools
 .

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Alberto Simões

Papers

The adaptation of the Affective Norms for English Words (ANEW) for European Portuguese

NATools, a statistical word aligner workbench

On the advantages of word frequency and contextual diversity measures extracted from subtitles: The case of Portuguese.

jspell.pm: um módulo de análise morfológica para uso em processamento de linguagem natural

Procura-PALavras (P-PAL): A Web-based interface for a new European Portuguese lexical database