Dans le contexte général de la résolution de problèmes inverses en acoustique et traitement du signal audio les défis sont nombreux. Pour la résolution de ces problèmes, leur caractère souvent mal posé nécessite de considérer des modèles de signaux appropriés. Les travaux de cette thèse montrent sur la base d'un cadre algorithmique générique polyvalent comment les différentes formes de parcimonie (à l'analyse ou à la synthèse, simple, structurée ou sociale) sont particulièrement adaptées à la reconstruction de signaux sonores dans un cadre mono ou multicanal. Le cœur des travaux de thèse permet de mettre en évidence les limites des conditions d'évaluation de l'état de l'art pour le problème de désaturation et de mettre en place un protocole rigoureux d'évaluation à grande échelle pour identifier les méthodes les plus appropriées en fonction du contexte (musique ou parole, signaux fortement ou faiblement dégradés). On démontre des améliorations de qualité substantielles par rapport à l'état de l'art dans certains régimes avec des configurations qui n'avaient pas été précédemment considérées, nous obtenons également des accélérations conséquentes. Enfin, un volet des travaux aborde la localisation de sources sonores sous l'angle de l'apprentissage statistique « virtuellement supervisé ». On montre avec cette méthode des résultats encourageants sur l'estimation de directions d'arrivée et de distance. / Today's challenges in the context of audio and acoustic signal processing inverse problems are multiform. Addressing these problems often requires additional appropriate signal models due to their inherent ill-posedness. This work focuses on designing and evaluating audio reconstruction algorithms. Thus, it shows how various sparse models (analysis, synthesis, plain, structured or “social”) are particularly suited for single or multichannel audio signal reconstruction. The core of this work notably identifies the limits of state-of-the-art methods evaluation for audio declipping and proposes a rigourous large-scale evaluation protocol to determine the more appropriate methods depending on the context (music or speech, moderately or highly degraded signals). Experimental results demonstrate substantial quality improvements for some newly considered testing configurations. We also show computational efficiency of the different methods and considerable speed improvements. Additionally, a part of this work is dedicated to the sound source localization problem. We address it with a “virtually supervised” machine learning technique. Experiments show with this method promising results on distance and direction of arrival estimation.

Thesis (MScEng)--University of Stellenbosch, 2003. / ENGLISH ABSTRACT: Two non-destructive methods of extracting audio from Edison phonographic cylinders were investigated. A recording device with high accuracy positioning was designed and manufactured. A microscopic image method was investigated first. Surface images of the cylinder were obtained using a webcamera. An audio signal was then extracted from the width modulation. Results were not pleasing as echoes caused by intergroove modulation were perceptable. The audio also lacked resolution. The true modulation of the audio is not embedded in the width, but in the depth of the groove. The second audio extraction method involved using a laser pick-up from a compact disc player to measure the depth of the groove. Three laser recording methods were investigated. The first was forward recording, that measured the depth modulation in the recording direction of the groove. The second method, backward recording, was identical to forward recording with the mechanical system moving in reverse. Four recordings from different positions in the groove were combined to create an audio signal. This combination of recordings showed a substantial improvement in the signal-to-noise ratio. A third recording method, transverse recording, that measured the whole depth profile of the groove was also investigated. The groove profile was then processed to an audio signal. A manual audio restoration program was written to replace visible sections of distorted data with better interpolations. Two speech enhancement methods were investigated, the first being the most commonly used speech enhancement method for digital audio restoration, Short-Time Spectral Attenuation (STSA). The second method is based on linear predictive coefficient (LPC) estimation of short-time frames. The two methods were evaluated by means of listening tests. The LPC enhancement method was preferred because it enhanced the intelligibility of the speech. / AFRIKAANSE OPSOMMING: Twee nie-destruktiewe metodes om klank van Edison-fonograafsilinders te onttrek, is ondersoek. 'n Opneemtoestel, wat die silinders met baie hoë akkuraatheid posisioneer, IS ontwerp en vervaardig. 'n Mikroskopiese beeldrnetode IS as eerste klankonttrekkingsmetode ondersoek. Mikroskopiese beelde is met 'n webkamera van die silinderoppervlak geneem. Klank is vanuit die wydtemodulasie sigbaar in die beelde onttrek. Resultate was nie bevredigend nie weens groefintermodulasie-eggo's en 'n tekort aan resolusie. Die ware modulasie van die klank is nie in die wydte van die groefie gegraveer nie, maar in die diepte. Die tweede klankonttrekkingsmetode gebruik 'n aangepaste lasersensor van 'n CD-speler om die dieptemodulasie van die groefie te meet. Drie laseropneemmetodes is ondersoek. Die eerste is voorwaartse opname, wat die dieptemodulasie in die opneemrigting van die groefie meet. 'n Tweede opneemmetode, truwaartse opname, is identies aan voorwaartse opname, behalwe dat die meganiese stelsel in trurat beweeg. Vier opnames vanuit verskillende posisies in die groefbreedte is gekombineer om 'n klanksein te vorm. Die kombinasie van vier opnames toon 'n beduidende verbetering op die sein-tot-ruis-verhouding. Dit het aanleiding gegee tot die derde opneemmetode, dwarsskandering, wat die hele profiel van die groef meet. Die groefprofiel word dan verwerk tot 'n klanksein. 'n Handoudiorestourasieprogram is geskryf om sigbare verwringing in die klanksein met beter interpolasies te vervang. Twee spraakverheffingsmetodes is ondersoek. Short- Time Spectral Attenuation (STSA) is die mees gebruikte metode vir oudiorestourasie. 'n Tweede spraakverheffingsmetode wat van 'n lineêre voorspellingskoëffisiëntafskatting (LPC-afskatting) van korttydraampies gebruik maak, is ook toegepas. Die twee metodes is deur luistertoetse teen mekaar opgeweeg. Die LPCmetode is verkies aangesien dit die verstaanbaarheid van die spraak beter behoue laat bly.

V oblasti zpracování signálů se v současné době čím dál více využívají tzv. řídké reprezentace signálů, tzn. že daný signál je možné vyjádřit přesně či velmi dobře aproximovat lineární kombinací velmi malého počtu vektorů ze zvoleného reprezentačního systému. Tato práce se zabývá využitím řídkých reprezentací pro rekonstrukci poškozených zvukových záznamů, ať už historických nebo nově vzniklých. Především historické zvukové nahrávky trpí zarušením jako praskání nebo šum. Krátkodobé poškození zvukových nahrávek bylo doposud řešeno interpolačními technikami, zejména pomocí autoregresního modelování. V nedávné době byl představen algoritmus s názvem Audio Inpainting, který řeší doplňování chybějících vzorků ve zvukovém signálu pomocí řídkých reprezentací. Zmíněný algoritmus využívá tzv. hladové algoritmy pro řešení optimalizačních úloh. Cílem této práce je porovnání dosavadních interpolačních metod s technikou Audio Inpaintingu. Navíc, k řešení optimalizačních úloh jsou využívány algoritmy založené na l1-relaxaci, a to jak ve formě analyzujícího, tak i syntetizujícího modelu. Především se jedná o proximální algoritmy. Tyto algoritmy pracují jak s jednotlivými koeficienty samostatně, tak s koeficienty v závislosti na jejich okolí, tzv. strukturovaná řídkost. Strukturovaná řídkost je dále využita taky pro odšumování zvukových nahrávek. Jednotlivé algoritmy jsou v praktické části zhodnoceny z hlediska nastavení parametrů pro optimální poměr rekonstrukce vs. výpočetní čas. Všechny algoritmy popsané v práci jsou na praktických příkladech porovnány pomocí objektivních metod odstupu signálu od šumu (SNR) a PEMO-Q. Na závěr je úspěšnost rekonstrukce poškozených zvukových signálů vyhodnocena.

The thesis deals with modern methods of audio denoising. Reconstruction of the audiosignal is primarly based on utilization of phase information of signals and phase derivatives. Denoising methods also use sparse signal representations. In thesis is described the way of searching sparse coefficients using proximal Condat algorithm and following computation of reconstructed signal using this coefficients. The reconstruction algorithms are implemented in the MATLAB software with toolbox LTFAT included. Results of the reconstruction are compared using objective evaluation method Signal-to-Noise Ratio (SNR) and also by subjective evaluation.

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Visualization, processing and editing of audio, directly on a time-frequency surface, is the scope of this thesis. More precisely the scalogram produced by a Gabor Wavelet transform is used, which is a powerful alternative to traditional techinques where the wave form is the main visual aid and editting is performed by parametric filters. Reconstruction properties, scalogram design and enhancements as well audio manipulation algorithms are investigated for this audio representation.The scalogram is designed to allow a flexible choice of time-frequency ratio, while maintaining high quality reconstruction. For this mean, the Loglet is used, which is observed to be the most suitable filter choice.  Re-assignmentare tested, and a novel weighting function using partial derivatives of phase is proposed.  An audio interpolation procedure is developed and shown to perform well in listening tests.The feasibility to use the transform coefficients directly for various purposes is investigated. It is concluded that Pitch shifts are hard to describe in the framework while noise thresh holding works well. A downsampling scheme is suggested that saves on operations and memory consumption as well as it speeds up real world implementations significantly. Finally, a Scalogram 'compression' procedure is developed, allowing the caching of an approximate scalogram.

The dissertation thesis focuses on objective assessment and reduction of disturbing background noise in a musical signal. In this work, a new algorithm for the assessment of background noise audibility is proposed. The listening tests performed show that this new algorithm better predicts the background noise audibility than the existing algorithms do. An advantage of this new algorithm is the fact that it can be used even in the case of a general audio signal and not only musical signal, i.e. in the case when the audibility of one sound on the background of another sound is assessed. The existing algorithms often fail in this case. The next part of the dissertation thesis deals with an adaptive segmentation scheme for the segmentation of long-term musical signals into short segments of different lengths. A new adaptive segmentation scheme is then introduced here. It has been shown that this new adaptive segmentation scheme significantly improves the subjectively perceived quality of the musical signal from the output of noise reduction systems which use this new adaptive segmentation scheme. The quality improvement is better than that achieved by other segmentation schemes tested.