Music shapelets for fast cover song regognition

A cover song is a new performance or recording of a previously recorded music by an artist other than the original one. The automatic identification of cover songs is useful for a wide range of tasks, from fans looking for new versions of their favorite songs to organizations involved in licensing copyrighted songs. This is a difficult task given that a cover may differ from the original song in key, timbre, tempo, structure, arrangement and even language of the vocals. Cover song identification has attracted some attention recently. However, most of the state-of-the-art approaches are based on similarity search, which involves a large number of similarity computations to retrieve potential cover versions for a query recording. In this paper, we adapt the idea of time series shapelets for contentbased music retrieval. Our proposal adds a training phase that finds small excerpts of feature vectors that best describe each song. We demonstrate that we can use such small segments to identify cover songs with higher identification rates and more than one order of magnitude faster than methods that use features to describe the whole music.FAPESP (grants #2011/17698-5, #2013/26151-5, and 2015/07628-0)CNPq (grants 446330/2014-0 and 303083/2013-1

Marketing, qualidade e inovação.

Texto publicado originalmente no jornal Açoriano Oriental, secção "Bits & Bytes", de 18 de Novembro de 2006."[…]. Marketing é, segundo a nova definição da associação americana (American MarketingAssociation), um conjunto de actividades que têm por objectivo compreender as necessidades do consumidor, cliente ou utente e de empreender esforços para satisfazer essas necessidades, da melhor forma possível, ou seja, de forma a aumentar o valor dos produtos e serviços para os clientes, passando por melhorar o grau de satisfação, a fidelização e a satisfação global destes. O marketing surge assim como um conjunto de actividades absolutamente essenciais nas organizações modernas orientadas para o cliente e não para o produto ou serviço que vendem. O marketing é o ponto final da cadeia logística, sendo responsável por objectivos definidos em termos de volume de vendas ou da relação prolongada no tempo com o cliente. […]"

Automatic classification of laparos call and playback tests at cuniculture nests

The vocal behavior of rabbit pups was monitored during their first 15 days of life. It was possible to estimate the average of vocalizations issued in the nest by correlation calculations applied to spectrographic images. We performed experimental tests of playback and observed the behavior between the offspring and the doe during the period of lactation. The vocalizations can be important in pup recognition and consequently, stimulate the doe to nurse their offspring, decreasing the rate of mortality in the breeding phase

Automatic classification of drum sounds with indefinite pitch

Automatic classification of musical instruments is an important task for music transcription as well as for professionals such as audio designers, engineers and musicians. Unfortunately, only a limited amount of effort has been conducted to automatically classify percussion instrument in the last years. The studies that deal with percussion sounds are usually restricted to distinguish among the instruments in the drum kit such as toms vs. snare drum vs. bass drum vs. cymbals. In this paper, we are interested in a more challenging task of discriminating sounds produced by the same percussion instrument. Specifically, sounds from different drums cymbals types. Cymbals are known to have indefinite pitch, nonlinear and chaotic behavior. We also identify how the sound of a specific cymbal was produced (e.g., roll or choke movements performed by a drummer). We achieve an accuracy of 96.59% for cymbal type classification and 91.54% in a classification problem with 12 classes which represent the cymbal type and the manner or region that the cymbals are struck. Both results were obtained with Support Vector Machine algorithm using the Line Spectral Frequencies as audio descriptor. We believe that our results can be useful for a more detailed automatic drum transcription and for other related applications as well for audio professionals.Fundação de Amparo a Pesquisa e Desenvolvimento do Estado de São Paulo (FAPESP) (grants 2011/17698-5

Extracting texture features for time series classification

Time series are present in many pattern recognition applications related to medicine, biology, astronomy, economy, and others. In particular, the classification task has attracted much attention from a large number of researchers. In such a task, empirical researches has shown that the 1-Nearest Neighbor rule with a distance measure in time domain usually performs well in a variety of application domains. However, certain time series features are not evident in time domain. A classical example is the classification of sound, in which representative features are usually present in the frequency domain. For these applications, an alternative representation is necessary. In this work we investigate the use of recurrence plots as data representation for time series classification. This representation has well-defined visual texture patterns and their graphical nature exposes hidden patterns and structural changes in data. Therefore, we propose a method capable of extracting texture features from this graphical representation, and use those features to classify time series data. We use traditional methods such as Grey Level Co-occurrence Matrix and Local Binary Patterns, which have shown good results in texture classification. In a comprehensible experimental evaluation, we show that our method outperforms the state-ofthe-art methods for time series classification.CNPqFAPESP (grants #2011/17698-5, #2012/07295-3, #2012/50714-7 and #2013/23037-7

Satisfação de agentes afectivos no processo de tomada de decisão em grupo

Um dos factores mais determinantes para o sucesso de uma organização é a qualidade das decisões tomadas. Para que as decisões tomadas sejam melhores e potenciem a competitividade das organizações, sistemas como os Sistemas de Apoio à Tomada de Decisão em Grupo (SADG) têm sido fortemente desenvolvidos e estudados nas últimas décadas. Cada vez mais, estes sistemas são populados com um maior número de dados, com o objectivo de serem mais assertivos. Considera-se que com determinados dados seja possível que o sistema possa aferir a satisfação dos participantes com as decisões tomadas, tendencialmente de forma automática. Hoje em dia, as análises de satisfação com as decisões não contemplam na sua maioria factores imprescindíveis, como os emocionais e de personalidade, sendo que os modelos existentes tendem a ser incompletos. Nesta dissertação propõe-se uma metodologia que permite a um SADG aferir a satisfação do participante com a decisão, considerando aspectos como a personalidade, as emoções e as expectativas. A metodologia desenvolvida foi implementada num SADG (ArgEmotionsAgents) com uma arquitectura multiagente, composto por agentes que reflectem participantes reais e que estão modelados com a sua personalidade. De acordo com a sua personalidade, esses agentes trocam argumentos persuasivos de forma a obterem uma decisão consensual. No processo de troca de argumentos os agentes geram emoções que afectam o seu humor. A implementação da metodologia no ArgEmotionsAgents permite que, no final de uma reunião, seja possível aferir a satisfação dos agentes participantes com a decisão final e com o processo que levou à tomada de decisão. De forma a validar a metodologia proposta bem como a implementação que foi desenvolvida, foram realizadas quatro experiências em diferentes cenários. Numa primeira experiência, foi aferida a satisfação dos quatro agentes participantes. Nas experiências seguintes, um dos agentes participantes foi usado como referência e foram alteradas configurações (expectativas, personalidade e reavaliação das alternativas) para perceber de que forma os vários factores afectam a satisfação. Com o estudo concluiu-se que todos os factores considerados no modelo afectam a satisfação. A forma como a satisfação é afectada por cada um dos factores vai ao encontro da lógica apresentada no estado da arte. Os resultados de satisfação aferidos pelo modelo são congruentes.One of the most important factors to determine the success of an organization is the quality of decisions that are made. In order to improve the decisions taken and to strengthen the competitiveness of organizations, systems such as Group Decision Support Systems (GDSS) have been strongly developed and studied in recent decades. More data have been increasingly added to these systems in order to be more assertive. It is considered that with certain data it is possible to the system to assess automatically the participants' satisfaction regarding the decisions made. Nowadays, most of the satisfaction with the decisions does not address essential factors such as emotions and personality, since the existing models tend to be incomplete. In this thesis, is proposed a theory that allows a GDSS to measure the participant’s satisfaction with the decision, considering aspects such as personality, emotions and expectations. The developed methodology was implemented in a GDSS (ArgEmotionsAgents) with a multiagent architecture consisting of agents that reflect the real participants and are modeled according to their personality. According to their personality, these agents exchange persuasive arguments in order to take a consensual decision. In the process of exchanging arguments agents generate emotions that affect their mood. The implementation of the methodology in the ArgEmotionsAgents allows, at the end of the meeting, the possibility to measure the participants’ satisfaction with the final decision and with the process that led to the decision making. In order to validate the proposed methodology, as well the developed implementation, four experiments were performed in different scenarios. In a first experiment, the satisfaction of the four participating agents was measured. In the following experiments, one of participating agents was used as a reference and settings were changed (expectations, personality and alternatives re-evaluation) to understand how the several factors affect satisfaction. With this study we concluded that all factors considered in the model affect satisfaction. The way satisfaction is affected by each of the factors meets the logic presented in the state of the art. The results of satisfaction measured by the model are congruent

Time series transductive classification on imbalanced data sets: an experimental study

Graph-based semi-supervised learning (SSL) algorithms perform well on a variety of domains, such as digit recognition and text classification, when the data lie on a low-dimensional manifold. However, it is surprising that these methods have not been effectively applied on time series classification tasks. In this paper, we provide a comprehensive empirical comparison of state-of-the-art graph-based SSL algorithms with respect to graph construction and parameter selection. Specifically, we focus in this paper on the problem of time series transductive classification on imbalanced data sets. Through a comprehensive analysis using recently proposed empirical evaluation models, we confirm some of the hypotheses raised on previous work and show that some of them may not hold in the time series domain. From our results, we suggest the use of the Gaussian Fields and Harmonic Functions algorithm with the mutual k-nearest neighbors graph weighted by the RBF kernel, setting k = 20 on general tasks of time series transductive classification on imbalanced data sets.São Paulo Research Foundation (FAPESP) (grants 2011/17698-5 and 2012/50714-7

Desenvolvimento neuropsicomotor na infância e eventos obstétricos

Objective: Investigate and analyze the relationship between obstetric events and neuropsychomotor development in children aged 0 to 12 years. The research aims to contribute to understanding the impacts of these events on child development, providing insights that can guide obstetric practices, early interventions, and strategies for promoting health in childhood.Introduction: Contextualization and relevance of the study, addressing the importance of understanding the influence of obstetric events on neuropsychomotor child development. The need to explore this relationship is emphasized to inform obstetric practices and intervention strategies that promote healthy development in childhood. Methodology: Searches were conducted in the PubMed, Scielo, and Latindex databases using terms related to neuropsychomotor development and obstetric events. The DeCS terms used included "Neurology," "Growth and Development," "Child Development," "Obstetric Delivery," "Child Psychiatry," and "Adverse Birth Outcomes," combined with boolean operators AND and OR. Conclusion: The conclusion highlights the relationship between obstetric events and neuropsychomotor development. Understanding risk factors guides prevention and personalized interventions, addressing neonatal vulnerability. Evaluation and diagnosis are vital for adapted support, and therapeutic interventions drive progress. Emphasis on prevention, family support, research, and advocacy is crucial for inclusive environments and healthy development.Objetivo: Investigar e analisar a relação entre eventos obstétricos e o desenvolvimento neuropsicomotor em crianças de 0 a 12 anos. A pesquisa visa contribuir para a compreensão dos impactos desses eventos no desenvolvimento infantil, fornecendo insights que possam orientar práticas obstétricas, intervenções precoces e estratégias de promoção da saúde na infância. Introdução: Contextualização e relevância do estudo, abordando a importância de compreender a influência dos eventos obstétricos no desenvolvimento neuropsicomotor infantil. Destaca-se a necessidade de explorar essa relação para informar práticas obstétricas e estratégias de intervenção que promovam um desenvolvimento saudável na infância. Metodologia: Foram conduzidas buscas nas bases de dados PubMed, Scielo e Latindex usando termos relacionados ao desenvolvimento neuropsicomotor e eventos obstétricos. Os DeCs utilizados incluíram "Neurologia", "Crescimento e Desenvolvimento", "Desenvolvimento Infantil", "Parto Obstétrico", "Psiquiatria Infantil" e "Desfechos Adversos do Nascimento", combinados por operadores booleanos AND e OR. Conclusão: A conclusão destaca a relação entre eventos obstétricos e desenvolvimento neuropsicomotor. Entender fatores de risco guia prevenção e intervenções personalizadas, atendendo à vulnerabilidade neonatal. Avaliação e diagnóstico são vitais para suporte adaptado, e intervenções terapêuticas impulsionam o progresso. A ênfase em prevenção, suporte familiar, pesquisa e advocacia é crucial para ambientes inclusivos e o desenvolvimento saudável

<b>A comparative study between MFCC and LSF coefficients in automatic recognition of isolated digits pronounced in Portuguese and English</b> - doi: 10.4025/actascitechnol.v35i4.19825

<p class="aTitulodoArtigo">Recognition of isolated spoken digits is the core procedure for a large number of applications which rely solely on speech for data exchange, as in telephone-based services, such as dialing, airline reservation, bank transaction and price quotation. Spoken digit recognition is generally a challenging task since the signals last for a short period of time and often some digits are acoustically very similar to other digits. The objective of this paper is to investigate the use of machine learning algorithms for spoken digit recognition and disclose the free availability of a database with digits pronounced in English and Portuguese to the scientific community. Since machine learning algorithms are fully dependent on predictive attributes to build precise classifiers, we believe that the most important task for successfully recognizing spoken digits is feature extraction. In this work, we show that Line Spectral Frequencies (LSF) provide a set of highly predictive coefficients. We evaluated our classifiers in different settings by altering the sampling rate to simulate low quality channels and varying the number of coefficients.</p><p class="aresumo"><strong> </strong></p> <p class="apalavrachave"> </p