The Use of Bakhtin\u27s Polyphony to Analyze Peer Relationships

Abstract The purpose of this study was to examine how resident assistants integrate training on leadership and ethics with their personal beliefs in their roles as resident assistants (RAs). Data for this study was gathered using an electronic survey. Participants who have between one and four years of RA experience were to participate in this study. An announcement of the study with a link to the survey was sent to the resident director of all dorms on the UA campus with the request that the announcement be forwarded to the RAs. The survey included six questions that provided basic demographic information and training experience. Then the demographics was followed by four scenarios, each having four multiple choice options and two open ended questions about leadership and ethical action. It took approximately 10-20 minutes to complete the survey. Results were analyzed descriptively

Prosody, polyphony and politeness: A polyphonic approach to prosodic configurations common to French and Spanish

From a theoretical perspective based on the Theory of Argumentation in Language (Théorie de l’Argumentation dans la Langue – TAL) and the Theory of Polyphony (Théorie de la Polyphonie Énonciative – TPE), the present study describes and analyses polyphonic configurations that are disclosed through the use of certain voice traits; configurations which, unmistakably common to both French and Spanish, are manifested by what is said and what is prosodically shown in utterances. Within a French corpus and a Spanish corpus of naturally occurring discourse, the patent polyphonic dimension of intonation has been explored in order to demonstrate that locutors’ utterances themselves reveal the orientation of enunciation through both the marking of the lexical and grammatical components and the prosody within which they are embedded. Through this study, the authors show how the locutor – the discursive character presented by the utterance as responsible for its enunciation – puts on stage a multiplicity of enunciators, or viewpoints, which allow him or her to protect the image of self, i.e., the locutor’s own image, and expose, protect or enhance that of others. Polyphony is materialized in two different ways: one in which the enunciator embodied in the prosody reinforces the locutor’s assimilation to the wording of the utterance and another in which the enunciator corresponding to the intonational feature does not match what is expressed through words.Fil: Garcia Negroni, Maria Marta. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Universidad de Buenos Aires. Facultad de Filosofía y Letras. Instituto de Lingüística; ArgentinaFil: Caldiz, Adriana Mabel. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación; Argentina. Universidad Nacional de La Plata. Facultad de Humanidades y Ciencias de la Educación. Departamento de Lenguas Modernas; Argentin

Multiple-F0 estimation of piano sounds exploiting spectral structure and temporal evolution

This paper proposes a system for multiple fundamental frequency estimation of piano sounds using pitch candidate selection rules which employ spectral structure and temporal evolution. As a time-frequency representation, the Resonator Time-Frequency Image of the input signal is employed, a noise suppression model is used, and a spectral whitening procedure is performed. In addition, a spectral flux-based onset detector is employed in order to select the steady-state region of the produced sound. In the multiple-F0 estimation stage, tuning and inharmonicity parameters are extracted and a pitch salience function is proposed. Pitch presence tests are performed utilizing information from the spectral structure of pitch candidates, aiming to suppress errors occurring at multiples and sub-multiples of the true pitches. A novel feature for the estimation of harmonically related pitches is proposed, based on the common amplitude modulation assumption. Experiments are performed on the MAPS database using 8784 piano samples of classical, jazz, and random chords with polyphony levels between 1 and 6. The proposed system is computationally inexpensive, being able to perform multiple-F0 estimation experiments in realtime. Experimental results indicate that the proposed system outperforms state-of-the-art approaches for the aforementioned task in a statistically significant manner. Index Terms: multiple-F0 estimation, resonator timefrequency image, common amplitude modulatio

Acoustic event detection for multiple overlapping similar sources

Many current paradigms for acoustic event detection (AED) are not adapted to the organic variability of natural sounds, and/or they assume a limit on the number of simultaneous sources: often only one source, or one source of each type, may be active. These aspects are highly undesirable for applications such as bird population monitoring. We introduce a simple method modelling the onsets, durations and offsets of acoustic events to avoid intrinsic limits on polyphony or on inter-event temporal patterns. We evaluate the method in a case study with over 3000 zebra finch calls. In comparison against a HMM-based method we find it more accurate at recovering acoustic events, and more robust for estimating calling rates.Comment: Accepted for WASPAA 201

Joint Multi-Pitch Detection Using Harmonic Envelope Estimation for Polyphonic Music Transcription

In this paper, a method for automatic transcription of music signals based on joint multiple-F0 estimation is proposed. As a time-frequency representation, the constant-Q resonator time-frequency image is employed, while a novel noise suppression technique based on pink noise assumption is applied in a preprocessing step. In the multiple-F0 estimation stage, the optimal tuning and inharmonicity parameters are computed and a salience function is proposed in order to select pitch candidates. For each pitch candidate combination, an overlapping partial treatment procedure is used, which is based on a novel spectral envelope estimation procedure for the log-frequency domain, in order to compute the harmonic envelope of candidate pitches. In order to select the optimal pitch combination for each time frame, a score function is proposed which combines spectral and temporal characteristics of the candidate pitches and also aims to suppress harmonic errors. For postprocessing, hidden Markov models (HMMs) and conditional random fields (CRFs) trained on MIDI data are employed, in order to boost transcription accuracy. The system was trained on isolated piano sounds from the MAPS database and was tested on classic and jazz recordings from the RWC database, as well as on recordings from a Disklavier piano. A comparison with several state-of-the-art systems is provided using a variety of error metrics, where encouraging results are indicated

Edward Said and the Margins

Edward Said was the quintessential intellectual of the last quarter of the twentieth century. Commonly celebrated as the founding figure of postcolonialism, his critical oeuvre spans varied terrain. The very strength of his critique lies in these diverse tributaries of thought. Crossing borders and boundaries incessantly, Said’s intellectual project celebrates the culture of resistance while opposing doctrinaire rhetoric. The paper tries to journey along the multifarious “margins” of discourses that crop up in Said. “In-between” spaces have to be investigated for their radical potential, while daring to “transgress” has its own dangers. Said unmasks the unholy nexus between knowledge and power in the mapping of the “Orient” that abetted the colonial enterprise. His contrapuntal readings of literary texts reveal the ubiquitous presence of imperial empire. Consequently, voices from the margins spur counter narratives and “writing back” in the postcolonial condition. Intellectuals in exile tend to be “marginal” and this location helps in looking at the two or even three sides of an issue. Questions of identity, selfhood, nationality, politics, memory, history, representation, geography, homeland, anxieties of influence are dealt with in the paper. The intertwining of the personal and the political occurs in Said. “Memory” is the only hope for resuscitating a “lost world” and battling the accompanying sense of “loss” and “despair” infused in both individuals and communities alike. The paper tries to address how “border crossing” and the “coalescing of margins” create an interdisciplinary breadth in Said, which resist categorization. The “centre/margin” binary is problematized by acknowledging the presence of “many voices,” “polyphony” being a favourite concept of Said. Music gave to him metaphors for human emancipation, while “transgression” was vital. His acknowledgement and assimilation of fellow critics is also mentioned. Beyond enunciating insider-outsider distinctions, Said tried to cultivate knowledge as a bridge between different interests and locations

Multi-label Ferns for Efficient Recognition of Musical Instruments in Recordings

In this paper we introduce multi-label ferns, and apply this technique for automatic classification of musical instruments in audio recordings. We compare the performance of our proposed method to a set of binary random ferns, using jazz recordings as input data. Our main result is obtaining much faster classification and higher F-score. We also achieve substantial reduction of the model size

Boylan's Fugue in 'Sirens'

Recent discoveries in genetic studies require a revision of the fugal structure in ‘Sirens.’ We hope we can shed light on some of the remaining unsolved questions by applying these studies to an interdisciplinary approach. We will put forward our point of view on the most controversial debate on music in Joyce: does this episode of Ulysses contain the eight parts of a fuga per canonem, as the author asserted, and how can we find these parts. Our study is based on the The Sirens Copybook manuscript authenticated by Michael Groden, as well as on the further analysis by two scholars, Daniel Ferrer and Susan Brown. We believe that the role of the character Blazes Boylan in ‘Sirens’ is crucial to divide the episode in eight parts chronologically. First of all, we must point out that some of the concepts that are being used for this interdisciplinary analysis are not unambiguous and depend on the field of study alluded to. A good example is the notion of “theme,” which appears in literature as the main subject of a text, but in music it is understood as a synonym for motif, the musical material that provides a work with its own identity. Some problems of interpretation arise when this term is applied in both music and literature without a clear distinction, such as in the discussion of the eight fugal parts in ‘Sirens.’ Two authors – Stuart Gilbert and Susan Brown – claim to identify these eight sections by mentioning the “themes.” Also, the accuracy of an interdisciplinary study depends on the meticulous use of homogenous sources for the musical concepts. If not, one may argue that the scholar quotes one dictionary or another depending on his/her own interests. Susan Brown recently established that Joyce’s musical knowledge was based on the Grove’s Dictionary of Music (in this paper we will be using the abbreviation GDM). Despite detractors of Brown’s thesis, like Michelle Witen, we believe that for all practical purposes this encyclopaedia is the most useful source for establishing a standardised musical terminology. Every definition of a musical term for this research has been taken from this source

Features for the classification and clustering of music in symbolic format

Tese de mestrado, Engenharia Informática, Universidade de Lisboa, Faculdade de Ciências, 2008Este documento descreve o trabalho realizado no âmbito da disciplina de Projecto em Engenharia Informática do Mestrado em Engenharia Informática da Faculdade de Ciências da Universidade de Lisboa. Recuperação de Informação Musical é, hoje em dia, um ramo altamente activo de investigação e desenvolvimento na área de ciência da computação, e incide em diversos tópicos, incluindo a classificação musical por géneros. O trabalho apresentado centra-se na Classificação de Pistas e de Géneros de música armazenada usando o formato MIDI. Para resolver o problema da classificação de pistas MIDI, extraimos um conjunto de descritores que são usados para treinar um classificador implementado através de uma técnica de Máquinas de Aprendizagem, Redes Neuronais, com base nas notas, e durações destas, que descrevem cada faixa. As faixas são classificadas em seis categorias: Melody (Melodia), Harmony (Harmonia), Bass (Baixo) e Drums (Bateria). Para caracterizar o conteúdo musical de cada faixa, um vector de descritores numérico, normalmente conhecido como ”shallow structure description”, é extraído. Em seguida, eles são utilizados no classificador — Neural Network — que foi implementado no ambiente Matlab. Na Classificação por Géneros, duas propostas foram usadas: Modelação de Linguagem, na qual uma matriz de transição de probabilidades é criada para cada tipo de pista midi (Melodia, Harmonia, Baixo e Bateria) e também para cada género; e Redes Neuronais, em que um vector de descritores numéricos é extraído de cada pista, e é processado num Classificador baseado numa Rede Neuronal. Seis Colectâneas de Musica no formato Midi, de seis géneros diferentes, Blues, Country, Jazz, Metal, Punk e Rock, foram formadas para efectuar as experiências. Estes géneros foram escolhidos por partilharem os mesmos instrumentos, na sua maioria, como por exemplo, baixo, bateria, piano ou guitarra. Estes géneros também partilham algumas características entre si, para que a classificação não seja trivial, e para que a robustez dos classificadores seja testada. As experiências de Classificação de Pistas Midi, nas quais foram testados, numa primeira abordagem, todos os descritores, e numa segunda abordagem, os melhores descritores, mostrando que o uso de todos os descritores é uma abordagem errada, uma vez que existem descritores que confundem o classificador. Provou-se que a melhor maneira, neste contexto, de se classificar estas faixas MIDI é utilizar descritores cuidadosamente seleccionados. As experiências de Classificação por Géneros, mostraram que os Classificadores por Instrumentos (Single-Instrument) obtiveram os melhores resultados. Quatro géneros, Jazz, Country, Metal e Punk, obtiveram resultados de classificação com sucesso acima dos 80% O trabalho futuro inclui: algoritmos genéticos para a selecção de melhores descritores; estruturar pistas e musicas; fundir todos os classificadores desenvolvidos num único classificador.This document describes the work carried out under the discipline of Computing Engineering Project of the Computer Engineering Master, Sciences Faculty of the Lisbon University. Music Information Retrieval is, nowadays, a highly active branch of research and development in the computer science field, and focuses several topics, including music genre classification. The work presented in this paper focus on Track and Genre Classification of music stored using MIDI format, To address the problem of MIDI track classification, we extract a set of descriptors that are used to train a classifier implemented by a Neural Network, based on the pitch levels and durations that describe each track. Tracks are classified into four classes: Melody, Harmony, Bass and Drums. In order to characterize the musical content from each track, a vector of numeric descriptors, normally known as shallow structure description, is extracted. Then they are used as inputs for the classifier which was implemented in the Matlab environment. In the Genre Classification task, two approaches are used: Language Modeling, in which a transition probabilities matrix is created for each type of track (Melody, Harmony, Bass and Drums) and also for each genre; and an approach based on Neural Networks, where a vector of numeric descriptors is extracted from each track (Melody, Harmony, Bass and Drums) and fed to a Neural Network Classifier. Six MIDI Music Corpora were assembled for the experiments, from six different genres, Blues, Country, Jazz, Metal, Punk and Rock. These genres were selected because all of them have the same base instruments, such as bass, drums, piano or guitar. Also, the genres chosen share some characteristics between them, so that the classification isn’t trivial, and tests the classifiers robustness. Track Classification experiments using all descriptors and best descriptors were made, showing that using all descriptors is a wrong approach, as there are descriptors which confuse the classifier. Using carefully selected descriptors proved to be the best way to classify these MIDI tracks. Genre Classification experiments showed that the Single-Instrument Classifiers achieved the best results. Four genres achieved higher than 80% success rates: Jazz, Country, Metal and Punk. Future work includes: genetic algorithms; structurize tracks and songs; merge all presented classifiers into one full Automatic Genre Classification System