Thesis (M.Ed.) -- Memorial University of Newfoundland. 1975. / Typescript. Bibliography : leaves 14-15. Also available online.

Originally presented as the author's Thesis (doctoral--Justus Liebig-Universität Giessen, 1983) under the title: Zur gesellschaftlichen Reichweite entwicklungspolitischer Bildungsarbeit mit Film und audiovisuellen Basismedien. / Includes bibliographical references (p. 400-426).

Thesis (Ph. D.)--University of Wisconsin-Madison. / Photocopy of typescript. Ann Arbor, Mich. : University Microfilms International, 1981. -- ix, 394 leaves, [3] folded leaves ; 22 cm. eContent provider-neutral record in process. Description based on print version record. Includes bibliographies.

Dans cette thèse, nous abordons le problème de la séparation de sources audio dans des mélanges convolutifs multicanaux et sous-déterminés,en utilisant une modélisation probabiliste.Nous nous concentrons sur trois aspects,et nous apportons trois contributions.D’abord, nous nous inspirons du modèle Gaussien local par factorisation en matrices non-négatives (LGM-with-NMF), qui est un modéle empiriquement validé pour représenter un signal audio.Nous proposons une extension Bayésienne de ce modèle, qui permet de surpasser certaines limitations du modèle NMF. Nous incorporons cette représentation dans un cadre de séparation audio multicanaux, et le comparons avec l’état de l’art sur des tâches de séparation. Nous obtenons des résultats prometteurs. Deuxièmement, nous étudions comment séparer des mélanges audio de sources et/ou des capteurs en mouvement. Ces déplacements rendent le chemin acoustique entre les sources et les microphones variant en cours du temps.L’adressage des mélanges convolutifs et variant au cours du temps semble rare dans la littérature. Ainsi, nous partons d’une méthode état de l’art utilisant LGM-with-NMF, développée pour la séparation de mélanges invariants (sources et microphones statiques). Nous proposons a ceci une extension qui utilise un filtre de Kalman pour suivre le chemin acoustique au cours du temps.La méthode proposée est comparée à une adaptation bloc par bloc d’une méthode de l’état de l’art appliquée sur des intervalles de temps,et adonné des résultats exceptionnels sur les mélanges simulés et les mélanges du monde réel. Enfin, nous investiguons les similitudes entre la séparation et la diarisation audio. La diarisation audio est le problème de l’annotation des intervalles d’un mélange audio, auxquels chaque locuteur/source est émettant. La plupart des méthodes de séparation supposent toutes les sources à émettant continuellement. Une hypothèse qui peut donner lieu à de fausses estimations,durant les intervalles au cours desquels cette source n’émettait pas. Notre objectif est que diarisation puisse aider à résoudre la séparation, en indiquant les sources qui émettent chaque intervalle de temps.Dans cette mesure, nous concevons une cadre commun pour traiter simultanément la diarisation et la séparation du mélange audio. Ce cadre incorpore,un modèle de Markov caché pour suivre les activités des sources,au sein d’une méthode de séparation LGM-with-NMF.Nous comparons l’algorithme proposé, à l’état de l’art sur des tâches de séparation et de diarisation. Nous obtenons des performances comparables avec l’état de l’art pour la séparation, et supérieures pour la diarisation. / In this thesis we address the problem of audio source separation (ASS) for multichannel and underdetermined convolutive mixtures through probabilistic modeling. We focus on three aspects of the problem and make three contributions. Firstly, inspired from the empirically well validated representation of an audio signal, that is know as local Gaussian signal model (LGM) with non-negative matrix factorization (NMF), we propose a Bayesian extension to this, that overcomes some of the limitations of the NMF. We incorporate this representation in a multichannel ASS framework and compare it with the state of the art in ASS, yielding promising results.Secondly, we study how to separate mixtures of moving sources and/or of moving microphones.Movements make the acoustic path between sources and microphones become time-varying.Addresing time-varying audio mixtures appears is not so popular in the ASS literature.Thus, we begin from a state of the art LGM-with-NMF method designed for separating time-invariant audiomixtures and propose an extension that uses a Kalman smoother to track the acoustic path across time.The proposed method is benchmarked against a block-wise adaptation of that state of the art (ran on time segments),and delivers competitive results on both simulated and real-world mixtures.Lastly, we investigate the link between ASS and the task of audio diarisation.Audio diarisation is the recognition of the time intervals of activity of every speaker/source in the mix.Most state of the art ASS methods consider the sources ceaselssly emitting; A hypothesis that can result in spurious signal estimates for a source, in intervals where that source was not emitting.Our aim is that diarisation can aid ASS by indicating the emitting sources at each time frame.To that extent we design a joint framework for simultaneous diarization and ASS,that incorporates a hidden Markov model (HMM) to track the temporal activity of the sources, within a state of the art LGM-with-NMF ASS framework.We compare the proposed method with the state of the art in ASS and audio diarisation tasks.We obtain performances comparable, with the state of the art, in terms of separation and outperformant in terms of diarisation.

Cette thèse s'inscrit dans le contexte de l'analyse/transformation/synthèse des signaux audio utilisant des représentations temps-fréquence, de type transformation de Gabor. Dans ce contexte, la complexité des transformations permettant de relier des sons peut être modélisée au moyen de multiplicateurs de Gabor, opérateurs de signaux linéaires caractérisés par une fonction de transfert temps-fréquence, à valeurs complexes, que l'on appelle masque de Gabor. Les multiplicateurs de Gabor permettent deformaliser le concept de filtrage dans le plan temps-fréquence. En agissant de façon multiplicative dans le plan temps-fréquence, ils sont a priori bien adaptés pour réaliser des transformations sonores telles que des modifications de timbre des sons. Dans un premier temps, ce travail de thèses intéresse à la modélisation du problème d'estimation d'un masque de Gabor entre deux signaux donnés et la mise en place de méthodes de calculs efficaces permettant de résoudre le problème. Le multiplicateur de Gabor entre deux signaux n'est pas défini de manière unique et les techniques d'estimation proposées de construire des multiplicateurs produisant des signaux sonores de qualité satisfaisante. Dans un second temps, nous montrons que les masques de Gabor contiennent une information pertinente capable d'établir une classification des signaux,et proposons des stratégies permettant de localiser automatiquement les régions temps-fréquence impliquées dans la différentiation de deux classes de signaux. Enfin, nous montrons que les multiplicateurs de Gabor constituent tout un panel de transformations sonores entre deux sons, qui, dans certaines situations, peuvent être guidées par des descripteurs de timbre / Analysis/Transformation/Synthesis is a generalparadigm in signal processing, that aims at manipulating or generating signalsfor practical applications. This thesis deals with time-frequencyrepresentations obtained with Gabor atoms. In this context, the complexity of a soundtransformation can be modeled by a Gabor multiplier. Gabormultipliers are linear diagonal operators acting on signals, andare characterized by a time-frequency transfer function of complex values, called theGabor mask. Gabor multipliers allows to formalize the conceptof filtering in the time-frequency domain. As they act by multiplying in the time-frequencydomain, they are "a priori'' well adapted to producesound transformations like timbre transformations. In a first part, this work proposes to model theproblem of Gabor mask estimation between two given signals,and provides algorithms to solve it. The Gabor multiplier between two signals is not uniquely defined and the proposed estimationstrategies are able to generate Gabor multipliers that produce signalswith a satisfied sound quality. In a second part, we show that a Gabor maskcontain a relevant information, as it can be viewed asa time-frequency representation of the difference oftimbre between two given sounds. By averaging the energy contained in a Gabor mask, we obtain a measure of this difference that allows to discriminate different musical instrumentsounds. We also propose strategies to automaticallylocalize the time-frequency regions responsible for such a timbre dissimilarity between musicalinstrument classes. Finally, we show that the Gabor multipliers can beused to construct a lot of sounds morphing trajectories,and propose an extension

This project deals with the subject of laboratory preparation for low-frequency and audio electronics. It is used DSP audio processor with integrated ADCs and DACs converters ADAU1701 from Analog Devices. Also, Atmel microcontroller with a connected graphic LCD display and buttons is used for adjusting DSP. The work presents the complete instructions of the laboratory project with a model protocol.

In the creation of my thesis project, I aimed to record a collection of music that highlights my influences and creative voice as an artist within the bluegrass/acoustic music genres. In collaboration with friends and colleagues that I have met during my time at East Tennessee State University, I have successfully recorded a project that surveys my current influences and creative voice as an artist, instrumentalist and composer. One goal I had for this project was to highlight compositions that I have written on acoustic guitar. Before attending ETSU, I did play some acoustic guitar, though I was primarily a banjo player. Since then, I have developed a passion for the guitar and have worked to advance my skills as a guitarist. My project includes two pieces that I composed on the guitar, and these compositions are examples of my exploration of harmony and rhythm. I feel that these pieces fit into the “New Acoustic” subgenre of bluegrass and bluegrass-adjacent music. I also chose to include two songs that fit more into the “progressive bluegrass” subgenre. On these two selections, one cover and one original, I played five-string banjo. These two pieces highlight my current interests and influences from genres like Jazz, Indie, and Pop music. The last two pieces included are songs that come from the bluegrass genre, and represent my progress as both an instrumentalist and vocalist. Also on this project, I experimented with different audio recording techniques. I have been studying audio production as my concentration within the Bluegrass, Old-Time, and Roots Music Studies major. This project allowed me to be creative as an audio engineer as well as a musician.

No description available.

The Interactive Video Data System (IVDS) project began with an initial abstract concept of achieving interactive television by transmitting hidden digital information in the audio of commercials. Over the course of three years such a communication method was successfully developed, the hardware systems to realize the application were designed and built, and several full-scale field tests were conducted. The novel coding scheme satisfies all of the design constraints imposed by the project sponsors. By taking advantage of psychoacoustic properties, the hidden digital signature is inaudible to most human observers yet is detectable by the hardware decoder. The communication method is also robust against most extraneous room noise as well as the wow and flutter of videotape machines. The hardware systems designed for the application have been tested and work as intended. A triple-stage audio amplifier buffers the input signal, eliminates low frequency interference such as human voices, and boosts the filtered result to an appropriate level. A codec samples the filtered and amplified audio, and feeds it into the digital signal processor. The DSP, after applying a pre-emphasis and compensation filter, performs the data extraction by calculating FFTs, compensating for frequency shifts, estimating the digital signature, and verifying the result via a cyclic redundancy check. It then takes action appropriate for the command specified in the digital signature. If necessary it will verbally prompt and provide information to the user, and will decode infrared signals from a remote control. The results of interactions are transmitted by radio frequency spread spectrum to a cell cite, where they are then forwarded to the host computer. / Master of Science

No description available.