RUSSIAN ACCENT IN BRAZILIAN PORTUGUESE AFFECTS THE PERCEPTION OF VOICE PLEASANTNESS BY BRAZILIANS

The field of foreign accents in Brazilian Portuguese is very poorly explored mainly in relation to perceptual impressions caused on listeners by foreign accents. The objective of this paper is to conduct a perceptual experiment to analyze the perception of voice pleasantness in relation to degrees of foreign accent. Our focus is on Russian accented Brazilian Portuguese. Despite the representativeness of the Russian community in Brazil, there are hardly any studies on Russian accented speech. To evaluate the perception of voice pleasantness in relation to the Russian accented speech, we have selected, from our database, speech samples in Brazilian Portuguese from 12 native Russian speakers and six Brazilians, all of them residing in São Paulo. The speech samples were incorporated into an online questionnaire. The analysis of the 129 answers given by the native Brazilian Portuguese speakers showed a strong negative correlation between the degree of Russian accent in Brazilian Portuguese and the degree of voice pleasantness. Experience of interaction with foreigners or knowledge of foreign languages, including Russian, did not influence the result. We conclude that higher degrees of Russian accented speech in Brazilian Portuguese affect the perception of speakers´ characteristics by Brazilians in a negative way

An investigation of genetic algorithm-based feature selection techniques applied to keystroke dynamics biometrics

Due to the continuous use of social networks, users can be vulnerable to online situations such as paedophilia treats. One of the ways to do the investigation of an alleged pedophile is to verify the legitimacy of the genre that it claims. One possible technique to adopt is keystroke dynamics analysis. However, this technique can extract many attributes, causing a negative impact on the accuracy of the classifier due to the presence of redundant and irrelevant attributes. Thus, this work using the wrapper approach in features selection using genetic algorithms and as KNN, SVM and Naive Bayes classifiers. Bringing as best result the SVM classifier with 90% accuracy, identifying what is most suitable for both bases

Fusing Audio, Textual and Visual Features for Sentiment Analysis of News Videos

This paper presents a novel approach to perform sentiment analysis of news videos, based on the fusion of audio, textual and visual clues extracted from their contents. The proposed approach aims at contributing to the semiodiscoursive study regarding the construction of the ethos (identity) of this media universe, which has become a central part of the modern-day lives of millions of people. To achieve this goal, we apply state-of-the-art computational methods for (1) automatic emotion recognition from facial expressions, (2) extraction of modulations in the participants' speeches and (3) sentiment analysis from the closed caption associated to the videos of interest. More specifically, we compute features, such as, visual intensities of recognized emotions, field sizes of participants, voicing probability, sound loudness, speech fundamental frequencies and the sentiment scores (polarities) from text sentences in the closed caption. Experimental results with a dataset containing 520 annotated news videos from three Brazilian and one American popular TV newscasts show that our approach achieves an accuracy of up to 84% in the sentiments (tension levels) classification task, thus demonstrating its high potential to be used by media analysts in several applications, especially, in the journalistic domain.Comment: 5 pages, 1 figure, International AAAI Conference on Web and Social Medi

Good practices for a literature survey are not followed by authors while preparing scientific manuscripts

The number of citations received by authors in scientific journals has become a major parameter to assess individual researchers and the journals themselves through the impact factor. A fair assessment therefore requires that the criteria for selecting references in a given manuscript should be unbiased with respect to the authors or the journals cited. In this paper, we advocate that authors should follow two mandatory principles to select papers (later reflected in the list of references) while studying the literature for a given research: i) consider similarity of content with the topics investigated, lest very related work should be reproduced or ignored; ii) perform a systematic search over the network of citations including seminal or very related papers. We use formalisms of complex networks for two datasets of papers from the arXiv repository to show that neither of these two criteria is fulfilled in practice

Acoustic correlates of linguistic rhythm: Perspectives

The empirical grounding of a typology of languages' rhythm is again a hot issue. The currently popular approach is based on the durations of vocalic and intervocalic intervals and their variability. Despite some successes, many questions remain. The main findings still need to be generalised to much larger corpora including many more languages. But a straightforward continuation of the current work faces many difficulties. Perspectives are outlined for future work, including proposals for the cross-linguistic control of speech rate, improvements on the statistical analyses, and prospects raised by automatic speech processing

The Latin Music Database

In this paper we present the Latin Music Database, a novel database of Latin musical recordings which has been developed for automatic music genre classification, but can also be used in other music information retrieval tasks. The method for assigning genres to the musical recordings is based on human expert perception and therefore capture their tacit knowledge in the genre labeling process. We also present the ethnomusicology of the genres available in the database as it might provide important information for the analysis of the results of any experiment that employs the database

A Cross-Linguistic Preference For Torso Stability In The Lexicon: Evidence From 24 Sign Languages

When the arms move in certain ways, they can cause the torso to twist or rock. Such extraneous torso movement is undesirable, especially during sign language communication, when torso position may carry linguistic significance, so we expend effort to resist it when it is not intended. This so-called “reactive effort” has only recently been identified by Sanders and Napoli (2016), but their preliminary work on three genetically unrelated languages suggests that the effects of reactive effort can be observed cross-linguistically by examination of sign language lexicons. In particular, the frequency of different kinds of manual movements in the lexicon correlates with the amount of reactive effort needed to resist movement of the torso. Following this line of research, we present evidence from 24 sign languages confirming that there is a cross-linguistic preference for minimizing the reactive effort needed to keep the torso stable