Audio on Demand

Jazz guitar solos are improvised melody lines played on one instrument on top of a chordal accompaniment (comping). As the improvisation happens spontaneously, a reference score is non-existent, only a lead sheet. There are situations, however, when one would like to have the original melody lines in the form of notated music, see the Real Book. The motivation is either for the purpose of practice and imitation or for musical analysis. In this work, an automatic transcriber for jazz guitar solos is developed. It resorts to a very intuitive representation of tonal music signals: the pitchgram. No instrument-specific modeling is involved, so the transcriber should be applicable to other pitched instruments as well. Neither is there the need to learn any note profiles prior to or during the transcription. Essentially, the proposed transcriber is a decision tree, thus a classifier, with a depth of 3. It has a (very) low computational complexity and can be run on-line. The decision rules can be refined or extended with no or little musical education. The transcriber's performance is evaluated on a set of ten jazz solo excerpts and compared with a state-of-the-art transcription system for the guitar plus PYIN. We achieve an improvement of 34 % w.r.t. the reference system and 19 % w.r.t. PYIN in terms of the F-measure. Another measure of accuracy, the error score, attests that the number of erroneous pitch detections is reduced by more than 50 % w.r.t. the reference system and by 45 % w.r.t. PYIN.

O podcast ao longo desses últimos anos vem ganhando espaço e conquistando o público, mostrando uma nova maneira de utilizar o áudio como ferramenta de se contar histórias. Com isso esse formato também se baseou em outras mídias, como a rádio, sendo a sua principal referência, porém utilizando a internet como meio de divulgação
e propagação.
Para comprovar a importância dos ruídos sonoros em podcast, utilizamos o episódio RPG Cyberpunk 1 “O Grande Assalto”, do Nerdcast. Com isso foi feita uma análise sonora, em que antes de nos aprofundarmos nos ruídos, também buscamos compreender
as características sonoras do gênero, a qual o episódio pertence. Por fazer parte do subgênero cyberpunk, a tecnologia se faz muito presente na narrativa e consequente no som.

Esse trabalho parte do pressuposto de que o jornalismo atua como narrador das próprias histórias em podcasts narrativos. Assim, o objetivo deste trabalho é olhar para o jornalismo enquanto participante ativo da narrativa e discorrer sobre sua representação, considerando sua potencial contribuição ao discurso da verdade nos relatos feitos em primeira pessoa pelo jornalista. A abordagem metodológica tem a narratologia como base, sendo  ela  estendida  e  relacionada  às  características  da  narrativa  sonora,  a  partir  do  narrador  do  radiodrama  (López-Vigil, 1997; Kaplún, 2017). Como objeto de pesquisa, recorremos à quarta temporada do podcast Projeto Humanos,  O  Caso  Evandro  para  que  se  investigue  o  papel  do  jornalismo  nessa  série.  Como  principal  contri-buição,  essa  pesquisa  aponta  a  emergência  do  jornalismo-narrador,  figura  que  também  conta  histórias  e  que,  portanto, compõe a trama principal

Non-negative Matrix Factorisation (NMF) is a commonly used tool in many musical signal processing tasks, including Automatic Music Transcription (AMT). However unsupervised NMF is seen to be problematic in this context, and harmonically constrained variants of NMF have been proposed. While useful, the harmonic constraints may be constrictive in mixed signals. We have previously observed that recovery of overlapping signal elements using NMF is improved through introduction of a sparse coding step, and propose here the incorporation of a sparse coding step using the Hellinger distance into a NMF algorithm. Improved AMT results for unsupervised NMF are reported.

In many studies devoted to the sound quality of industrial products, a perceptual space is determined through dissimilarity judgements on pairs of stimuli. A drawback of this procedure is that it can be very time consuming if the number of stimuli is large. An alternative procedure consists in a free sorting of sounds: averaging individual results provides a set of data which are considered as indicators of dissimilarities and analyzed using a multi-dimensional scaling method. The validity of this alternative can be discussed, as the psychological processes involved in the two procedures are different. This study compared these two approaches in a particular case (door closure sounds). In this specific case, it was observed that dissimilarities obtained from the two procedures can be different, the more so as sounds are dissimilar and these differences can lead to slightly different perceptual spaces. Nevertheless, a free sorting experiment is a reliable way of reducing the number of stimuli in a large set of sounds. It allows selecting some representative sounds and narrowing the set of sounds while keeping in the subset most of the timbre features. This provides a useful preliminary step to a paired-comparison experiment.

Aircraft interior noise is a major design stake with respect to airline requirements for passenger and crew comfort. The focus was put here on cockpit noise. The goal of this study was to evaluate unpleasantness of such sounds and to assess the relevance of existing metrics for its prediction. Six sounds recorded in various airplanes were used; one of them was modified in order to reduce the level of an emerging low-frequency component, leading to a number of seven stimuli. These stimuli were used in a pair-comparison experiment in a soundproof booth. 31 listeners participated to the experiment. Results could be analysed using a BTL model, which provided an unpleasantness scaling of the stimuli. Unpleasantness was clearly related to loudness. Predictions from two loudness models were investigated: the ISO-532 one and the ANSI S3.4 one. It appeared that the former gave better results. It is argued that this is due to the evolution of loudness values in the low frequency range, which is different between these two models.

Many studies have shown that industrial products can exhibit a great variability in their vibratory and acoustical behaviour; but the influence of this physical variability on the perception of sound emitted by these products has not yet been investigated. The aim of this study was to evaluate that influence in the case of a computed system, including a force source linked to a plate through three springs. The physical variability could affect the force amplitude, the stiffness of each spring, the thickness and damping of the plate. Two listening tests have been conducted : in the first one, a L 18 fractional designed experiment was used for the sounds synthesis; 20 listeners had to evaluate the similarity between each sound and a reference one (corresponding to the nominal state of the system). The most important factors were identified (force amplitude, plate thickness and the stiffness of one of the three springs); psychoacoustical criteria representing the perception were Zwicker loudness and Aures roughness. In the second test, 38 sounds (including the 18 used in the fractional design) were categorized by listeners according to their timbre similarity; a three-dimensional perceptual space was built from the answers. The plate thickness appeared to be more influent in that case and was linked to the first dimension of the perceptual space; it was related to a spectrum balance which could be correctly described from the specific loudness curves. Loudness and roughness still described the two other dimensions of the perceptual space.

This paper describes an original method for speech quality evaluation in the presence of different types of background noises for a range of communications (mobile, VoIP, RTC). The model is obtained from subjective experiments described in [1]. These experiments show that background noise can be more or less tolerated by listeners, depending on the sources of noise that can be identified. Using a classification method, the background noises can be classified into four groups. For each one of the four groups, a relation between loudness of the noise and speech quality is proposed.

This article studies a vital issue in wireless communications, which is the transmission of audio signals over wireless networks. It presents a novel interleaver scheme for protection against error bursts and reduction the packet loss of the audio signals. The proposed technique in the article is the chaotic interleaver; it is based on chaotic Baker map. It is used as a randomizing data tool to improve the quality of the audio over the mobile communications channels. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for audio transmission over uncorrelated and correlated fading channels is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes. The simulation results also reveal that the proposed chaotic interleaver improves the quality of the received audio signal. It improves the amount of the throughput over the wireless link through the packet loss reduction.

Binaural sound recordings in various positions in a high-speed train have been used as stimuli in listening tests. In a first experiment, sounds were submitted to subjects at their real levels. Loudness revealed to be the most important parameter; it could be very well described by Aweighted levels. In a second experiment, loudness of stimuli were equalised; strong interindividual differences appeared, which are due to different appreciations of the low-frequency content of sounds. Usual physical or psycho-acoustical parameters failed to correctly described that perceptual parameter; a simple parameter based on the specific loudness calculations was developed and could correctly describe the results.

The aim of this paper is to improve beat-tracking for live guitar performances. Beat-tracking is a function to estimate musical measurements, for example musical tempo and phase. This method is critical to achieve a synchronized ensemble performance such as musical robot accompaniment. Beat-tracking of a live guitar performance has to deal with three challenges: tempo fluctuation, beat pattern complexity and environmental noise. To cope with these problems, we devise an audiovisual integration method for beat-tracking. The auditory beat features are estimated in terms of tactus (phase) and tempo (period) by Spectro-Temporal Pattern Matching (STPM), robust against stationary noise. The visual beat features are estimated by tracking the position of the hand relative to the guitar using optical flow, mean shift and the Hough transform. Both estimated features are integrated using a particle filter to aggregate the multimodal information based on a beat location model and a hand's trajectory model. Experimental results confirm that our beat-tracking improves the F-measure by 8.9 points on average over the Murata beat-tracking method, which uses STPM and rule-based beat detection. The results also show that the system is capable of real-time processing with a suppressed number of particles while preserving the estimation accuracy. We demonstrate an ensemble with the humanoid HRP-2 that plays the theremin with a human guitarist.

In this paper psychoacoustic distances, or perceived differences, within sounds that differ from each other in terms of musical timbre are studied. The sounds were modified in four timbre dimensions: the ratio of even and odd harmonic components, brightness, the attack time, and the amount of noise. The psychoacoustic distances between the sounds differing only in timbre were evaluated through a subjective listening test. A set of sounds having an equal psychoacoustic distance from the reference sound was generated for a ...

Este trabalho analisa a quarta temporada do podcast Projeto Humanos, tendo como horizonte o uso da categoria de True Crime para a compreensão de produções  sonoras  brasileiras  sobre  crimes  reais.  A  abordagem  desenvolvida  coloca  em  diálogo  a  metodologia  proposta  por  Punnett  (2018)  para  a  análise textual de produções desse gênero com a noção de radiojornalismo narrativo (KISCHINHEVSKY, 2018). Como resultado, identificamos aspectos enunciativos e narrativos que permitem classificar esse podcast como um exemplar de True Crime e propomos reflexões acerca de particularidades da linguagem radiofônica para a construção desse tipo de narrativa

Este trabalho analisa a quarta temporada do podcast Projeto Humanos, tendo como horizonte o uso da categoria de True Crime para a compreensão de produções sonoras brasileiras sobre crimes reais. A abordagem desenvolvida coloca em diálogo a metodologia proposta por Punnett (2018) para a análise textual de produções desse gênero com a noção de radiojornalismo narrativo (KISCHINHEVSKY, 2018). Como resultado, identificamos aspectos enunciativos e narrativos que permitem classificar esse podcast como um exemplar de True Crime e propomos reflexões acerca de particularidades da linguagem radiofônica para a construção desse tipo de narrativa.

Em uma era da convergência de meios de comunicação, em que muitos afirmam que a rapidez do fluxo de informações proporcionadas por novas tecnologias estão causando um distanciamento entre os produtores e receptores de conteúdo, esta pesquisa tem como objetivo estudar como a plataforma online do podcast reproduz e ressignifica estratégias narrativas capazes de resgatar e renovar a paixão por contar histórias com profundidade. Para tal, utilizamos a metodologia de análise crítica da narrativa, proposta por Luiz Gonzaga Motta (2013), para estudar quais são as técnicas narrativas presentes nos cinco programas da primeira temporada do podcast de storytelling "Projeto Humanos" e de que forma elas operam para atrair, conquistar e fidelizar a audiência desejada. Para constatar esses fatores, é realizado um levantamento sobre como nós, como seres humanos, nos entendemos e articularmos sentidos por meio da comunicação narrativa. São apresentados métodos de estudo e registro narrativos, trabalhando conceitos como os de memória, história oral e entrevista. Também são descritos um histórico e um panorama sobre o podcast, uma plataforma de distribuição e transmissão de conteúdo que abriga o objeto empírico de análise desta pesquisa. Cientes de que essa plataforma está em constante expansão de seu alcance midiático, inclusive entre o público brasileiro, compreendemos que um estudo voltado para a elucidação de estratégias narrativas em podcasts é de interesse para o campo da comunicação, tanto o acadêmico, quanto o mercadológico. Entendemos, enfim, que, por mais que soe paradoxal, o meio digital pode contribuir, cada vez mais, para a propagação de narrativas mais humanizadas.

This paper addresses the problem of retrieval of mu-sical events from a performance. Current state of the art transcription and score following systems extract features from the audio signal which are used to estimate what has been played in order to transcribe or find a position ...

Esta pesquisa se desdobra a partir de quatro características do radiojornalismo narrativo em podcasting (KISHINHEVSKY, 2018): (1) A construção de uma narrativa potencialmente imersiva; (2) A emergência do narrador; (3) O uso de ganchos que remetem à dramaturgia; e (4) Uma apuração exaustiva. Tendo, então, como pressuposto o fato de que o áudio é imersivo por essência, o seguinte questionamento ilustra o problema de pesquisa: Quais estratégias utilizadas pelo narrador potencializam a experiência imersiva do ouvinte? Buscando repostas, o objetivo é olhar para a figura do narrador a fim de identificar e entender o seu lugar no que chamamos nesta tese de jornalismo narrativo em podcasting. A partir do pensamento de Aristóteles (2017) de que as personagens são, depois do enredo, o principal elemento da dramaturgia, também partimos do pressuposto que o próprio jornalismo, assim como o jornalista, compõe o quadro das personagens da história. Então, nossa hipótese é que nessas produções, o narrador vai além da retratação do ofício e da técnica ao acionar o metajornalismo, pois reforça o discurso da verdade presente nas narrativas em podcasts. Como abordagem metodológica, propomos uma adaptação à Análise Crítica da Narrativa (MOTTA, 2013a) levando em consideração a natureza e complexidade do objeto sonoro. O corpus dessa pesquisa é composto pela quarta temporada do podcast Projeto Humanos, intitulada O Caso Evandro. Como principal resultado, encontramos três principais estratégias que potencializam a experiência imersiva do ouvinte: aquelas que atuam com função estética; as que têm como função criar imagens mentais para o ouvinte através do som; e aquelas que têm como função criar laços afetivos. Assim, confirmando a hipótese, ao ser acionado pelo narrador, o metajornalismo não só vai além da retratação do ofício e da técnica, como também reforça o discurso da verdade presente nas narrativas. E, mais que isso, também se constitui como uma ponte que liga o posicionamento do narrador enquanto jornalista com uma figura humanizada, já que abre as portas para que sentimentos, como certezas e inseguranças, façam parte da história.

Trabalho de Conclusão de Curso (graduação)—Universidade de Brasília, Faculdade de Comunicação, Departamento de Jornalismo, 2020.Este Trabalho de Conclusão de Curso se volta à apresentação de todo o processo de realização do episódio-piloto da série de podcasts jornalísticos “Sotaques em Tela”, que visa ao debate sobre a representação da diversidade de falares regionais de telejornalistas nos noticiários nacionais. O referido piloto se dirige à abordagem conceitual e histórica da multiplicidade de sotaques no Brasil e a construção de um falar que é próprio do jornalismo televisivo. Assim, o estudo da pauta se deu à luz da Sociolinguística e da história do telejornalismo no Brasil. Como metodologia aplicada, a análise de conteúdo de produtos do mesmo estilo permitiu observar a aplicação de entrevistas como fio condutor do formato escolhido e os recursos jornalísticos empregados dentro de uma estrutura que permite novas formas de interação. Concluiu-se que a diversidade de sotaques bra...

This work explores areas overlapping music, graph theory, and machine learning. An embedding representation of a node, in a weighted undirected graph $\mathcal{G}$, is a representation that captures the meaning of nodes in an embedding space. In this work, 383 Bach chorales were compiled and represented as a graph. Two application cases were investigated in this paper (i) learning node embedding representation using \emph{Continuous Bag of Words (CBOW), skip-gram}, and \emph{node2vec} algorithms, and (ii) learning node labels from neighboring nodes based on a collective classification approach. The results of this exploratory study ascertains many salient features of the graph-based representation approach applicable to music applications.

Computation models that rely on a decision boundary approach have a severe limitation in recognizing the same objects with different appearances. Variations in the appearance of an object often create variations in their discriminative features as well. Hence, the derived feature data points might be shifted into the wrong decision regions. In this paper, we present an application of a dictionary-based Non-negative Matrix Factorization (NMF) for classifying handwritten digits under superimposition. The superimposed digits are encoded as the input V, which is factorized into two matrices, V ≈ WH where W is the basis vector representing the prototypes of handwritten digits and H is the encoding coefficients representing the digit classification output sequence. We show that a dictionary-based NMF could classify an input sequence of single handwritten digits as well as superimposed digits. This is because NMF searches for an optimal linear aggregation of the components in the dictionary V ≈ WH. This unique ability of NMF allows it to classify superimposed digits. The experimental results show that the proposed approach can recognize superimposed digits with good accuracy.

In this work we investigate the stability of a Bluetooth piconet operating in fading (Rice, Rayleigh or Nakagami) channels. By taking into account many protocol details, such as modulation scheme and packet formats, we provide an analytical characterization of the achievable rate regions, which, for a network of N nodes, turn out to be the interior of a convex polyhedron in a (2N-2)-dimensional space. We show also that some previous analysis of Bluetooth link performance, by neglecting the impact of the multiple access scheme, may lead to erroneous conclusions in terms of optimal packet format.

We present in this paper a new approach for polyphonic music transcription using evolution strategies (ES). Automatic music transcription is a complex process that still remains an open challenge. Using an audio signal to be transcribed as target for our ES, information needed to generate a MIDI file can be extracted from this latter one. Many techniques presented in the literature at present exist and a few of them have applied evolutionary algorithms to address this problem in the context of considering it as a search space problem. However, ES have never been applied until now. The experiments showed that by using these machines learning tools, some shortcomings presented by other evolutionary algorithms based approaches for transcription can be solved. They include the computation cost and the time for convergence. As evolution strategies use self-adapting parameters, we show in this paper that by correctly tuning the value of its strategy parameter that controls the standard de...

Product experience is a result of sensory and semantic experiences with product properties. In this paper, we focus on the semantic attributes of product sounds and explore the basic components for product sound related semantics using a semantic differential paradigm and factor analysis. With two experiments, we determined eight factors that underlie the semantic associations of product sounds (attention, roughness, smoothness, temporal constancy, (un)familiarity, unpleasantness, machinery, and power). Correlations of the results from both experiments indicate that perceptual factors (attention, roughness, smoothness, and temporal constancy) influence cognitive factors (power, machinery, and (un)familiarity) and emotional factors (unpleasantness).This finding suggests a hierarchical structure in the meaningful associations of product sounds. Furthermore, we have shown that product sound related semantics is sound type dependent.

In previous works in the field of Active Noise Control (ANC) applied to passenger car cavities, it has been shown that the psychoacoustic metric known as Loudness can be modified in a rather efficient manner, influencing the internal sound field and overall vehicle perception. In that sense, engine orders can be controlled either to have their amplitudes increase or decrease, which directly affects Loudness and might also indirectly influence other sound quality attributes. A rather important metric that should be targeted whenever engine noise is concerned, is Roughness. This paper aims at demonstrating that Roughness can be modified by means of an ANC system that changes amplitude and/or phase of certain engine orders, leading to the desired noise attributes targeted at the vehicle´s conceptual design phase. The proposed control scheme is implemented in the frequency domains with the aid of the Fx-LMS and also inspired in some recent developments such as the PSC-FxLMS and the NEX-LMS. The proposed frequency-domain active controller can tackle pure harmonic-level problems as well as more complex multi-harmonic problems thus presenting a complete sound quality control system that is able to explore a wide range of design possibilities in vehicle sound.

The perceptual evaluation of sound quality is a necessary step to dene acoustic specications for industrial products. However, usual procedures for this include experimental tasks where the participants are asked to perform their perceptual judgment while paying exclusive attention to the produced sound. As far as air-treatment systems (ATS) are concerned, this kind of task is not representative of the normal listening conditions. Indeed, ATS users are hearing the sound while performing other tasks that require partially or entirely their attention. In this study, a dedicated procedure was designed in order to address the inuence of the listener's attention towards the judged sound. This procedure includes a subsidiary task on the purpose of shifting the listener's attention away from the sound. Participants were then asked to evaluate a posteriori the acoustic comfort in terms of how much the sound interfered with the subsidiary task. The results of this experiment as regards sound preferences were nally compared to those obtained without the subsidiary task. This study was conducted through the Vaicteur Air 2 project supported by OSEO.

Identifying the temporal location of downbeats is a fundamental musical skill. After briefly discussing the perceptual information available in beat tracking, we survey previous attempts to automate this process in both real time and non-real time. Our attempt to add flexibility to Mont-Reynaud’s model [4] by parameterizing the confidence and history mechanisms failed to yield a satisfactory beat tracker. Observing that this and previous models are constrained to hold a single current notion of beat timing and placement, we find that they will fail to predict beats and not recover beyond the point at which a mistake is first made. We propose a new model that uses beam search [1] to simultaneously consider multiple interpretations of the performance. At any time, predictions of beat timing and placement can be made according to the most credible of many interpretations under consideration. Credibility is determined by a heuristic evaluation function. Introduction Identifying the temp...

Specifications of product sound qualities may contain both perceptual and acoustical descriptions. The perceptual descriptions are most helpful when they contain adequate detail and utilises understandable wording. To facilitate the product design process the descriptions should also be interpretable as acoustical quantities. The objectives of the study reported upon here were to investigate how musicians use verbal descriptions of sound and to interpret these descriptions in terms of commonly used acoustical quantities. Musicians' use of verbal descriptions of saxophone sound was investigated through interviews. The most frequently used words were evaluated through listening tests. The subjects were asked to judge how well the words described the timbre of test sounds. To find the most significant perceptual dimensions for the test sounds Principal Component Analysis was used. Four significant dimensions were found and described by 9 words. To interpret the perceptual dimension...

This article studies a vital issue in wireless communications, which is the transmission of audio signals over wireless networks. It presents a novel interleaver scheme for protection against error bursts and reduction the packet loss of the audio signals. The proposed technique in the article is the chaotic interleaver; it is based on chaotic Baker map. It is used as a randomizing data tool to improve the quality of the audio over the mobile communications channels. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for audio transmission over uncorrelated and correlated fading channels is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes. The simulation results also reveal that the proposed chaotic interleaver improves the quality of the received audio signal. It improves the amount of the throughput over the wireless link through the packet loss reduction.

This article presents a method of adjusting the tempo of a music software sequencer so that it remains synchronized with a drummer's musical pulse. This allows music sequencer technology to be integrated into a band scenario without the compromise of using click tracks or triggering loops with a fixed tempo. Our design implements real-time mechanisms for both underlying tempo and phase adjustment using adaptable parameters that control its behavior. The aim is to create a system that responds to timing variations in the drummer's playing but is also stable during passages of syncopation and fills. We present an evaluation of the system using a stochastic drum machine that incorporates a level of noise in the underlying tempo and phase of the beat. We measure synchronization error between the output of the system and the underlying pulse of the drum machine and contrast this with other real-time beat trackers. The software, B-Keeper, has been released as a Max for Live device...

Detecting beats, estimating tempo, aligning scores to audio, and detecting onsets are all interesting problems in the field of music information retrieval. In much of this research, it is convenient to think of beats as occuring at precise time points. However, anyone who has attempted to label beats by hand soon realizes that precise annotation of music audio is not possible. A common method of beat annotation is simply to tap along with audio and record the tap times. This raises the question: How accurate are the taps? It may seem that an answer to this question would require knowledge of "true" beat times. However, tap times can be characterized as a random distribution around true beat times. Multiple independent taps can be used to estimate not only the location of the true beat time, but also the statistical distribution of measured tap times around the true beat time. Thus, without knowledge of true beat times, and without even requiring the existence of precise beat times, we can estimate the uncertainty of tap times. This characterization of tapping can be useful for estimating tempo variation and evaluating alternative annotation methods.

This article studies a vital issue in wireless communications, which is the transmission of audio signals over wireless networks. It presents a novel interleaver scheme for protection against error bursts and reduction the packet loss of the audio signals. The proposed technique in the article is the chaotic interleaver; it is based on chaotic Baker map. It is used as a randomizing data tool to improve the quality of the audio over the mobile communications channels. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for audio transmission over uncorrelated and correlated fading channels is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes. The simulation results also reveal that the proposed chaotic interleaver improves the quality of the received audio signal. It improves the amount of the throughput over the wireless link through the packet loss reduction.

Resumo: Com o objetivo de identificar as dicas culturais do podcast Mamilos, no quadro Farol Aceso, durante o período da cobertura da Covid-19 no Brasil, este levantamento se estabelece na abordagem da reconfiguração comunicacional e do entretenimento em tempos de pandemia. Para análise, foram mapeados os meses de fevereiro, março e abril de 2020, que resultaram em 11 edições do podcast, com 49 indicações culturais. Para tal, foi utilizada Análise de Conteúdo, mediante a perspectiva quantitativa e interpretativa. Notou-se que 8 episódios estavam relacionados ao assunto coronavírus, com 43 indicações, tendo séries, livros e filmes como o entretenimento mais sugerido, na qual é possível afirmar a relação de tais sugestões com o tema do programa da semana.
Palavras-chave: Podcast Mamilos; Farol Aceso; Dicas Culturais; Pandemia. Reconfiguração Comunicacional.

Objetiva-se fornecer uma apresentação do podcast ‘Diários da Quarentena’, produzido em Goiânia, a partir da necessidade de compartilhar experiências sobre o período da pandemia. Desenvolveu-se uma reflexão analítica dos áudios recebidos para composição dos episódios do podcast a partir de experiências individuais daqueles que aceitaram participar da coletânea. Sendo o podcast uma mídia recente e inovadora, essa reflexão é feita com abordagem e metodologia qualitativa com uso da lógica indutiva após a escuta das produções. O texto também apresenta reflexões sobre a mídia podcast e sua potencialidade nos dias atuais.

Essa pesquisa pretende iniciar um debate acerca do uso da técnica storytelling para podcasts que se enquadram na categoria de radiojornalismo narrativo. Recorremos à revisão bibliográfica para refletir sobre o uso de tal estratégia na composição de narrativas e aplicamos a análise de conteúdo no primeiro episódio da quarta temporada do Projeto Humanos, “O Caso Evandro”, para aprofundar as discussões. Como principal resultado, observamos que, com base nas características do rádio e da mídia sonora, há um terreno propulsor para o desenvolvimento do storytelling.

This paper discusses about the creation of embedded musical scores, where one score generates another, done through the exploration of the transferal of human mechanical movement to robotic mechanical movement. Through the combination of these two mediums the topic of human-robotic musical interaction is explored with the first steps to a human-robot musical controller and performance. We also detail the progress of the first prototype with including the realization, different implementation issues for this kind of proposition and the potentiall forms in which this kind of project can be implemented better in the future.

Non-negative matrix factorization (NMF) is a commonly used method for audio source separation in applications such as polyphonic music separation and noise removal. Previous research evaluated the use of additional algorithmic components and systems in efforts to improve the effectiveness of NMF. This study examined how the short-time Fourier transform (STFT) window duration used in the algorithm might affect detectable differences in separation performance. An ABX listening test compared speech extracted from two types of noise-contaminated mixtures at different window durations to determine if listeners could discriminate between them. It was found that the window duration had a significant impact on subject performance in both white-and conversation-noise cases with lower scores for the latter condition.

To participate in classes of expositive content is in the agenda of any student, in any degree, basic, high school or graduation. Many teaching professionals try to “soften” such exposition of  content,  so  that  classes  become  less  boring  and  less  unproductive.  The  podcast  is  one  of such  tools  that  can  help  this  process.  Podcasts  are  radio  shows  distributed  digitally  by  RSS (HARRIS; REA, 2009) and, since the conception of the term (HEMMERSLEY, 2004), it has been used as a resource in classrooms (RAINSBURY, 2006), however not in a broadly way, this  research  helps  to  close  this  gap.  Focusing  on  the  study,  elaboration,  production  and distribution of podcasts, this paper seeks to show them as  Learning Objects,  in an e-learning course  of  scientific  paper  production applying  an  specific  method  fot  its  development, consisting  of  the  following  phases:  pre-production,  production  and  post-production  (MIRO, 2013a) (FOSCHINI E TADDEI, 2006). This podcasts was offered by LALETEC (Laboratory of  Technical-Scientific  Literacy),  at Instituto  Federal  de  Educacão  Ciência  e  Tecnologia  de São  Paulo, câmpusSão  João  da  Boa  Vista.  The  material  presents the  macro  and microstructures  of  the  Scientific  Text,  and contain  from broader matters to more  specific properties  of  the  Scientific  text  gender. The  Scientific  text  macrostructure  contains  the following  topics:  The  Scientific  Text  (gender:  theme,  composition,  style  and  argumentative type  of  text);  the  argumentative  text  (Aristotelle  model  of  Rethoric);  the  scientific  paper (sections);  the  development  (theoretical referential  and  metodology);  the  conclusion  (results and  discussion).  In the  textual  microstructure, the  expanded topics  are:  the  style  (discourse); the Brazilian abstract (by ABNT), the translated abstract (and the use of machine translation); the use of visual data (tables, boards, graphs, etc.); text cohesion (topic sentence / discursive markers). Such podcasts are presented from these discursive genders: interviews, discussions and even the adaptation of one of its discursive structures to a food recipe. The technical steps taken  to  the  construction  of  the  podcast  were  pre-production  (schedule),  production (recording)  and  post-production  (editing  and  distributing) (MIRO,  2013a)  (FOSCHINI  E TADDEI, 2006). The podcasts were distributed as support material through the methodology Flipped Learning, in which students have contact with the podcasts before going to classes. At the  end  of the  course  a  questionnaire  was filled  by the  students  and  only one  between  thirty two  students  did  not  approve  the  utilization  of  podcasts  in  the  course.  The materials distributed as podcasts are available through RSS, in order to be used for studying, as well as for helping in  new  academic  writing. It  was  concluded  that  it  is  easy  to  maintain  a  podcast, that  it  should  be  more  initiatives  in  the  creation  of  podcasts  for  academic  use,  focusing  not only in  the  writing of  scientific papers,  but in all courses,  and in every educational level.  As future  research  it  is  indicated  the  creation  of  a  comparative  study  in  order  to  evaluate  the quantitative gain of utilizing podcasts.

The wireless sensor networks different from classic wired networks, WMSN differs from other scalar network mainly nature and size of data transmitted, memory resources, and power consumption in each node for processing and transmission. The images broadcasting over wireless multimedia sensor networks that can be used in IEEE 802.15.4 (Zig-Bee) for short-range multimedia transmissions. In this paper a strong interleaver mechanism prepared to reduce or immune a burst error of network , this can be done by applying the chaotic interleaving on the pixel, bit ,and chip. The enhancement simulation for bit error rate and peak signal to noise ration by transceiver image cameraman though AWGN and Rayleigh fading channels are displayed. While transmitting the image by 20 dB signal to noise ratio on the Rayleigh fading channel, an improvement on the peak signal to noise ratio of the received image from 25.9 dB to 78.4 dB can be observed.

Listening tests like dissimilarity tests are traditionally used to study sound perception and build perceptive timbre spaces. As the processing of such tests is tedious when a large number of sounds are to be judged, this work proposes a method to automatically compute the dissimilarity between sounds by combining an auditory representation, the cochleagram, and the concept of time-frequency masks. The cochleagram gives an energy distribution in a timefrequency space which can be considered as a perceptive sound representation. By introducing auditory representations in time-frequency analysis, we wish to propose new tools to characterize timbre. Time-frequency masks that carry information about the time-frequency differences between two signals applied to auditory representations might lead to global timbre descriptors that, as opposed to most traditional timbre descriptors, also are adapted to signals that strongly evolve with time. In this study we applied the proposed method to engine sounds that are complex and rich signals whose perception strongly depends on the dynamic sound variation. In order to evaluate the robustness of our model, we compared the timbre space obtained with perceptive tests to the one generated by our proposed method.

This article studies a vital issue in wireless communications, which is the transmission of audio signals over wireless networks. It presents a novel interleaver scheme for protection against error bursts and reduction the packet loss of the audio signals. The proposed technique in the article is the chaotic interleaver; it is based on chaotic Baker map. It is used as a randomizing data tool to improve the quality of the audio over the mobile communications channels. A comparison study between the proposed chaotic interleaving scheme and the traditional block and convolutional interleaving schemes for audio transmission over uncorrelated and correlated fading channels is presented. The simulation results show the superiority of the proposed chaotic interleaving scheme over the traditional schemes. The simulation results also reveal that the proposed chaotic interleaver improves the quality of the received audio signal. It improves the amount of the throughput over the wireless link through the packet loss reduction. Figure 9 Received audio signal of file-1 waveform over a correlated fading channel (V c = 10 mile/h) at SNR = 20 dB. (a) No interleaving. (b) Bit-level interleaving. (c) Convolutional interleaving.

We present a probabilistic switching state space model for timing deviations in expressive music performance. We formulate tempo tracking and automatic transcription (rhythm quantization) as filtering and maximum a posteriori (MAP) state estimation tasks. The resulting model is suitable for real-time tempo tracking and transcription and hence useful in a number of music applications such as adaptive automatic accompaniment and score typesetting.

We introduce a framework for probabilistic generative models of time-frequency coefficients of audio signals, using a matrix factorization parametrization to jointly model spectral characteristics such as harmonicity and temporal activations and excitations. The models represent the observed data as the superposition of statistically independent sources, and we consider variance-based models used in source separation and intensity-based models for non-negative matrix factorization. We derive a generalized expectation-maximization algorithm for inferring the parameters of the model and then adapt this algorithm for the task of polyphonic transcription of music using labeled training data. The performance of the system is compared to that of existing discriminative and model-based approaches on a dataset of solo piano music.

The current study is part of a larger project aiming at offering intuitive mappings of control parameters piloting synthesis models by semantic descriptions of sounds, i.e. simple verbal labels related to various feelings, emotions, gestures or motions. Hence, this work is directly related to the general problem of semiotics of sounds. We here put a special interest in sounds evoking different perceived motions. In this paper, the experimental design of the listening tests is described and the results obtained from behavioural data are discussed. Then a set of signal descriptors is compared to categories using feature selection methods. A special interest is given to applications for sound synthesis.

Listening tests like dissimilarity tests are traditionally used to study sound perception and build perceptive timbre spaces. As the processing of such tests is tedious when a large number of sounds are to be judged, this work proposes a method to automatically compute the dissimilarity between sounds by combining an auditory representation, the cochleagram, and the concept of time-frequency masks. The cochleagram gives an energy distribution in a timefrequency space which can be considered as a perceptive sound representation. By introducing auditory representations in time-frequency analysis, we wish to propose new tools to characterize timbre. Time-frequency masks that carry information about the time-frequency differences between two signals applied to auditory representations might lead to global timbre descriptors that, as opposed to most traditional timbre descriptors, also are adapted to signals that strongly evolve with time. In this study we applied the proposed method to engine sounds that are complex and rich signals whose perception strongly depends on the dynamic sound variation. In order to evaluate the robustness of our model, we compared the timbre space obtained with perceptive tests to the one generated by our proposed method.

Quality investigations and design of interior car sounds constitute an important challenge for the car industry. Such sounds are complex and time-varying, inducing considerable timbre variations depending on the driving conditions. An interior car sound is indeed a mixture between several sound sources, with two main contributions, i.e. the engine noise, the aerodynamic and tire-road noise. That's why masking phenomena between these two components should be considered when studying perceptive attributes of interior car sounds. Additive synthesis is used to simulate the harmonic engine noise. Nevertheless, this synthesis is controlled by a large number of parameters and no relation between these parameters and their perceptive relevance has been clearly identified. By combining sensory analysis and signal analysis associated with an auditory model, we can find a relation between a reduced number of signal parameters and perceptive attributes. This study develops a method to simplify the timbre description of interior card sounds and presents the first results of auditory model application on such sounds.

The aim of the study is to transpose and extend to a set of environmental sounds the notion of sound descriptors usually used for musical sounds. Four separate primary studies dealing with interior car sounds, air-conditioning units, car horns, and closing car doors are considered collectively. The corpus formed by these initial stimuli is submitted to new experimental studies and analyses, both for revealing metacategories and for defining more precisely the limits of each of the resulting categories. In a second step, the new structure is modeled: common and specific dimensions within each category are derived from the initial results and new investigations of audio features are performed. Furthermore, an automatic classifier based on two audio descriptors and a multinomial logistic regression procedure is implemented and validated with the corpus.