970 resultados para Folk songs, English
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Song-selection and mood are interdependent. If we capture a song’s sentiment, we can determine the mood of the listener, which can serve as a basis for recommendation systems. Songs are generally classified according to genres, which don’t entirely reflect sentiments. Thus, we require an unsupervised scheme to mine them. Sentiments are classified into either two (positive/negative) or multiple (happy/angry/sad/...) classes, depending on the application. We are interested in analyzing the feelings invoked by a song, involving multi-class sentiments. To mine the hidden sentimental structure behind a song, in terms of “topics”, we consider its lyrics and use Latent Dirichlet Allocation (LDA). Each song is a mixture of moods. Topics mined by LDA can represent moods. Thus we get a scheme of collecting similar-mood songs. For validation, we use a dataset of songs containing 6 moods annotated by users of a particular website.
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Traditional taxonomy based on morphology has often failed in accurate species identification owing to the occurrence of cryptic species, which are reproductively isolated but morphologically identical. Molecular data have thus been used to complement morphology in species identification. The sexual advertisement calls in several groups of acoustically communicating animals are species-specific and can thus complement molecular data as non-invasive tools for identification. Several statistical tools and automated identifier algorithms have been used to investigate the efficiency of acoustic signals in species identification. Despite a plethora of such methods, there is a general lack of knowledge regarding the appropriate usage of these methods in specific taxa. In this study, we investigated the performance of two commonly used statistical methods, discriminant function analysis (DFA) and cluster analysis, in identification and classification based on acoustic signals of field cricket species belonging to the subfamily Gryllinae. Using a comparative approach we evaluated the optimal number of species and calling song characteristics for both the methods that lead to most accurate classification and identification. The accuracy of classification using DFA was high and was not affected by the number of taxa used. However, a constraint in using discriminant function analysis is the need for a priori classification of songs. Accuracy of classification using cluster analysis, which does not require a priori knowledge, was maximum for 6-7 taxa and decreased significantly when more than ten taxa were analysed together. We also investigated the efficacy of two novel derived acoustic features in improving the accuracy of identification. Our results show that DFA is a reliable statistical tool for species identification using acoustic signals. Our results also show that cluster analysis of acoustic signals in crickets works effectively for species classification and identification.
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This paper describes the development of the CU-HTK Mandarin Speech-To-Text (STT) system and assesses its performance as part of a transcription-translation pipeline which converts broadcast Mandarin audio into English text. Recent improvements to the STT system are described and these give Character Error Rate (CER) gains of 14.3% absolute for a Broadcast Conversation (BC) task and 5.1% absolute for a Broadcast News (BN) task. The output of these STT systems is then post-processed, so that it consists of sentence-like segments, and translated into English text using a Statistical Machine Translation (SMT) system. The performance of the transcription-translation pipeline is evaluated using the Translation Edit Rate (TER) and BLEU metrics. It is shown that improving both the STT system and the post-STT segmentations can lower the TER scores by up to 5.3% absolute and increase the BLEU scores by up to 2.7% absolute. © 2007 IEEE.
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[EN]This paper undertakes the study of the occurrence of non-corresponding demonstrative forms in Spanish, Basque and English in exactly the same linguistic context. It is proposed that the differenccs in the choice of the demonstratives result from the differences in the kind of iniormation that must be coded in each of the languages. Thus, I will argue that in Spanish and Basque the obligatory coding of the aspectual categories of the imperfect and the preterit has the function of imposing specific viewing arrangements onto the situations they designate. By contrast, in English, where the aspectual distinction is not overtly coded, the demonstrativcs are proposed to fulfil this function.
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[EN]In the newEuropean higher education space, Universities in Europe are exhorted to cultivate and develop multilingualism. The European Commission’s 2004–2006 action plan for promoting language learning and diversity speaks of the need to build an environment which is favourable to languages. Yet reality indicates that it is English which reigns supreme and has become the main foreign language used as means of instruction at European universities. Internationalisation has played a key role in this process, becoming one of the main drivers of the linguistic hegemony exerted by English. In this paper we examine the opinions of teaching staff involved in English-medium instruction, from pedagogical ecologyof-language and personal viewpoints. Data were gathered using group discussion. The study was conducted at a multilingual Spanish university where majority (Spanish), minority (Basque) and foreign (English) languages coexist, resulting in some unavoidable linguistic strains. The implications for English-medium instruction are discussed at the end of this paper.
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Case study on six partner organisations in the eastern region and how they have supported learners on apprenticeship and traineeship programmes.
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Santamaría, José Miguel; Pajares, Eterio; Olsen, Vickie; Merino, Raquel; Eguíluz, Federico (eds.)
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Santamaría, José Miguel; Pajares, Eterio; Olsen, Vickie; Merino, Raquel; Eguíluz, Federico (eds.)
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Santamaría, José Miguel; Pajares, Eterio; Olsen, Vickie; Merino, Raquel; Eguíluz, Federico (eds.)
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Eterio Pajares, Raquel Merino y José Miguel Santamaría (eds.)