932 resultados para Phonetic Similarity
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Despite knowing a familiar individual (such as a daughter) well, anecdotal evidence suggests that naming errors can occur among very familiar individuals. Here, we investigate the conditions surrounding these types of errors, or misnamings, in which a person (the misnamer) incorrectly calls a familiar individual (the misnamed) by someone else's name (the named). Across 5 studies including over 1,700 participants, we investigated the prevalence of the phenomenon of misnaming, identified factors underlying why it may occur, and tested potential mechanisms. We included undergraduates and MTurk workers and asked questions of both the misnamed and the misnamer. We find that familiar individuals are often misnamed with the name of another member of the same semantic category; family members are misnamed with another family member's name and friends are misnamed with another friend's name. Phonetic similarity between names also leads to misnamings; however, the size of this effect was smaller than that of the semantic category effect. Overall, the misnaming of familiar individuals is driven by the relationship between the misnamer, misnamed, and named; phonetic similarity between the incorrect name used by the misnamer and the correct name also plays a role in misnaming.
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Pós-graduação em Ciência da Computação - IBILCE
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The paper presents a computational analysis of Bulgarian dialect variation, concentrating on pronunciation differences. It describes the phonetic data set compiled during the project* ‘Measuring Linguistic Unity and Diversity in Europe’ that consists of the pronunciations of 157 words collected at 197 sites from all over Bulgaria. We also present the results of analyzing this data set using various quantitative methods and compare them to the traditional scholarship on Bulgarian dialects. The results have shown that various dialectometrical techniques clearly identify east-west division of the country along the ‘jat’ border, as well as the third group of varieties in the Rodopi area. The rest of the groups specified in the traditional atlases either were not confirmed or were confirmed with a low confidence.
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Aiming to ensure greater reliability and consistency of data stored in the database, the data cleaning stage is set early in the process of Knowledge Discovery in Databases (KDD) and is responsible for eliminating problems and adjust the data for the later stages, especially for the stage of data mining. Such problems occur in the instance level and schema, namely, missing values, null values, duplicate tuples, values outside the domain, among others. Several algorithms were developed to perform the cleaning step in databases, some of them were developed specifically to work with the phonetics of words, since a word can be written in different ways. Within this perspective, this work presents as original contribution an optimization of algorithm for the detection of duplicate tuples in databases through phonetic based on multithreading without the need for trained data, as well as an independent environment of language to be supported for this. © 2011 IEEE.
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Although developmental increases in the size of the position effect within a mispronunciation detection task have been interpreted as consistent with a view of the lexical restructuring process as protracted, the position effect itself might not be reliable. The current research examined the effects of position and clarity of acoustic-phonetic information on sensitivity to mispronounced onsets in 5- and 6-year-olds and adults. Both children and adults showed a position effect only when mispronunciations also differed in the amount of relevant acoustic-phonetic information. Adults' sensitivity to mispronounced second-syllable onsets also reflected the availability of acoustic-phonetic information. The implications of these findings are discussed in relation to the lexical restructuring hypothesis. (c) 2006 Elsevier Inc. All rights reserved.
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This paper presents a statistical comparison of regional phonetic and lexical variation in American English. Both the phonetic and lexical datasets were first subjected to separate multivariate spatial analyses in order to identify the most common dimensions of spatial clustering in these two datasets. The dimensions of phonetic and lexical variation extracted by these two analyses were then correlated with each other, after being interpolated over a shared set of reference locations, in order to measure the similarity of regional phonetic and lexical variation in American English. This analysis shows that regional phonetic and lexical variation are remarkably similar in Modern American English.
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Using an extended Prototype/Willingness Model, we examined the predictors of willingness to donate an organ to a partner/family member and a stranger while living. A questionnaire assessed university students’ (N = 284) attitudes, subjective norm, prototype favourability, prototype similarity, moral norm, and willingness to donate organs in each recipient scenario. All variables, except prototype favourability, predicted willingness to donate organs in both situations. Future strategies should emphasise perceived approval from important others for living donation, the consistency of living donation with one’s own morals, and encourage perceptions of similarity between oneself and living donors to increase acceptance of living donation.
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Spoken term detection (STD) popularly involves performing word or sub-word level speech recognition and indexing the result. This work challenges the assumption that improved speech recognition accuracy implies better indexing for STD. Using an index derived from phone lattices, this paper examines the effect of language model selection on the relationship between phone recognition accuracy and STD accuracy. Results suggest that language models usually improve phone recognition accuracy but their inclusion does not always translate to improved STD accuracy. The findings suggest that using phone recognition accuracy to measure the quality of an STD index can be problematic, and highlight the need for an alternative that is more closely aligned with the goals of the specific detection task.
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While spoken term detection (STD) systems based on word indices provide good accuracy, there are several practical applications where it is infeasible or too costly to employ an LVCSR engine. An STD system is presented, which is designed to incorporate a fast phonetic decoding front-end and be robust to decoding errors whilst still allowing for rapid search speeds. This goal is achieved through mono-phone open-loop decoding coupled with fast hierarchical phone lattice search. Results demonstrate that an STD system that is designed with the constraint of a fast and simple phonetic decoding front-end requires a compromise to be made between search speed and search accuracy.
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In this paper, we classify, review, and experimentally compare major methods that are exploited in the definition, adoption, and utilization of element similarity measures in the context of XML schema matching. We aim at presenting a unified view which is useful when developing a new element similarity measure, when implementing an XML schema matching component, when using an XML schema matching system, and when comparing XML schema matching systems.