1,720,970 research outputs found
Analyse et compréhension de l'évaluation des systèmes de reconnaissance automatique de la parole : vers des métriques intégrant la perception humaine
No full textWord error rate remains the main metric for evaluating automatic speech recognition (ASR) systems, but it does not always reflect human perception. This thesis proposes alternative metrics for evaluating not only spelling, but also grammar, semantics and phonetics. Using the HATS corpus, annotated by 143 French speakers, we measured the correlation between these metrics and human choices.The results show that SemDist, based on BERT's semantic representations, is the most relevant, while word error rate performs poorly. An analysis of the hyperparameters of ASR systems reveals that each metric evaluates distinct aspects, underlining the importance of multi-metric evaluation.Finally, to make semantic metrics more comprehensible, we developed the minED method, which identifies error severity and improves score interpretation, offering valuable tools for evaluating and perfecting ASR systems.Le taux d'erreur mot reste la métrique principale pour évaluer les systèmes de reconnaissance automatique de la parole (RAP), mais il ne reflète pas toujours la perception humaine. Cette thèse propose des métriques alternatives pour évaluer non seulement l'orthographe, mais aussi la grammaire, la sémantique et la phonétique. À travers le corpus HATS, annoté par 143 francophones, nous avons mesuré la corrélation entre ces métriques et les choix humains.Les résultats montrent que SemDist, basée sur les représentations sémantiques de BERT, est la plus pertinente, tandis que le taux d'erreur mot se révèle peu performant. Une analyse des hyperparamètres des systèmes de RAP révèle que chaque métrique évalue des aspects distincts, soulignant l'importance d'une évaluation multi-métrique.Enfin, pour rendre les métriques sémantiques plus compréhensibles, nous avons développé la méthode minED, qui identifie la gravité des erreurs et améliore l’interprétation des scores, offrant des outils précieux pour évaluer et perfectionner les systèmes RAP
Analyse et compréhension de l’évaluation des systèmes de reconnaissance automatique de la parole : vers des métriques intégrant la perception humaine
No full textWord error rate remains the main metric for evaluating automatic speech recognition (ASR) systems, but it does not always reflect human perception. This thesis proposes alternative metrics for evaluating not only spelling, but also grammar, semantics and phonetics. Using the HATS corpus, annotated by 143 French speakers, we measured the correlation between these metrics and human choices. The results show that SemDist, based on BERT’s semantic representations, is the most relevant, while word error rate performs poorly. An analysis of the hyperparameters of ASR systems reveals that each metric evaluates distinct aspects, underlining the importance of multi-metric evaluation. Finally, to make semantic metrics more comprehensible, we developed the minED method, which identifies error severity and improves score interpretation, offering valuable tools for evaluating and perfecting ASR systems.Le taux d’erreur mot reste la métrique principale pour évaluer les systèmes de reconnaissance automatique de la parole (RAP), mais il ne reflète pas toujours la perception humaine. Cette thèse propose des métriques alternatives pour évaluer non seulement l’orthographe, mais aussi la grammaire, la sémantique et la phonétique. À travers le corpus HATS, annoté par 143 francophones, nous avons mesuré la corrélation entre ces métriques et les choix humains. Les résultats montrent que SemDist, basée sur les représentations sémantiques de BERT, est la plus pertinente, tandis que le taux d’erreur mot se révèle peu performant. Une analyse des hyperparamètres des systèmes de RAP révèle que chaque métrique évalue des aspects distincts, soulignant l’importance d’une évaluation multi-métrique. Enfin, pour rendre les métriques sémantiques plus compréhensibles, nous avons développé la méthode minED, qui identifie la gravité des erreurs et améliore l’interprétation des scores, offrant des outils précieux pour évaluer et perfectionner les systèmes RAP
Analyse et compréhension de l’évaluation des systèmes de reconnaissance automatique de la parole : vers des métriques intégrant la perception humaine
No full textWord error rate remains the main metric for evaluating automatic speech recognition (ASR) systems, but it does not always reflect human perception. This thesis proposes alternative metrics for evaluating not only spelling, but also grammar, semantics and phonetics. Using the HATS corpus, annotated by 143 French speakers, we measured the correlation between these metrics and human choices. The results show that SemDist, based on BERT’s semantic representations, is the most relevant, while word error rate performs poorly. An analysis of the hyperparameters of ASR systems reveals that each metric evaluates distinct aspects, underlining the importance of multi-metric evaluation. Finally, to make semantic metrics more comprehensible, we developed the minED method, which identifies error severity and improves score interpretation, offering valuable tools for evaluating and perfecting ASR systems.Le taux d’erreur mot reste la métrique principale pour évaluer les systèmes de reconnaissance automatique de la parole (RAP), mais il ne reflète pas toujours la perception humaine. Cette thèse propose des métriques alternatives pour évaluer non seulement l’orthographe, mais aussi la grammaire, la sémantique et la phonétique. À travers le corpus HATS, annoté par 143 francophones, nous avons mesuré la corrélation entre ces métriques et les choix humains. Les résultats montrent que SemDist, basée sur les représentations sémantiques de BERT, est la plus pertinente, tandis que le taux d’erreur mot se révèle peu performant. Une analyse des hyperparamètres des systèmes de RAP révèle que chaque métrique évalue des aspects distincts, soulignant l’importance d’une évaluation multi-métrique. Enfin, pour rendre les métriques sémantiques plus compréhensibles, nous avons développé la méthode minED, qui identifie la gravité des erreurs et améliore l’interprétation des scores, offrant des outils précieux pour évaluer et perfectionner les systèmes RAP
Analyse et compréhension de l'évaluation des systèmes de reconnaissance automatique de la parole : vers des métriques intégrant la perception humaine
No full textWord error rate remains the main metric for evaluating automatic speech recognition (ASR) systems, but it does not always reflect human perception. This thesis proposes alternative metrics for evaluating not only spelling, but also grammar, semantics and phonetics. Using the HATS corpus, annotated by 143 French speakers, we measured the correlation between these metrics and human choices.The results show that SemDist, based on BERT's semantic representations, is the most relevant, while word error rate performs poorly. An analysis of the hyperparameters of ASR systems reveals that each metric evaluates distinct aspects, underlining the importance of multi-metric evaluation.Finally, to make semantic metrics more comprehensible, we developed the minED method, which identifies error severity and improves score interpretation, offering valuable tools for evaluating and perfecting ASR systems.Le taux d'erreur mot reste la métrique principale pour évaluer les systèmes de reconnaissance automatique de la parole (RAP), mais il ne reflète pas toujours la perception humaine. Cette thèse propose des métriques alternatives pour évaluer non seulement l'orthographe, mais aussi la grammaire, la sémantique et la phonétique. À travers le corpus HATS, annoté par 143 francophones, nous avons mesuré la corrélation entre ces métriques et les choix humains.Les résultats montrent que SemDist, basée sur les représentations sémantiques de BERT, est la plus pertinente, tandis que le taux d'erreur mot se révèle peu performant. Une analyse des hyperparamètres des systèmes de RAP révèle que chaque métrique évalue des aspects distincts, soulignant l'importance d'une évaluation multi-métrique.Enfin, pour rendre les métriques sémantiques plus compréhensibles, nous avons développé la méthode minED, qui identifie la gravité des erreurs et améliore l’interprétation des scores, offrant des outils précieux pour évaluer et perfectionner les systèmes RAP
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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