La modélisation sinusoïdale est une des méthodes les plus largement utilisés paramétriques pour la parole et le traitement des signaux audio. Inspiré par le récemment introduit Modèle aQHM et Modèle aHM, nous la vue d’ensemble de la théorie de l’ adaptation sinusoïdale modélisation et nous proposons un modèle nommé la Modèle eaQHM, qui est un non modèle paramétrique de mesure d’ajuster les amplitudes et les phases instantanées de ses fonctions de base aux caractéristiques variant dans le temps de sous-jacents du signal de parole, ainsi atténuer significativement la dite hypothèse de stationnarité locale. Le eaQHM est montré à surperformer aQHM dans l’analyse et la resynthèse de la parole voisée. Sur la base de la eaQHM , un système hybride d’analyse / synthèse de la parole est présenté (eaQHNM), et aussi d’ une version hybride de l’ aHM (aHNM). En outre, nous présentons la motivation pour une représentation pleine bande de la parole en utilisant le eaQHM, c’est, représentant toutes les parties du discours comme haute résolution des sinusoıdes AM-FM. Les expériences montrent que l’adaptation et la quasi-harmonicité est suffisante pour fournir une qualité de transparence dans la parole non voisée resynthèse. La pleine bande analyse eaQHM et système de synthèse est présenté à côté, ce qui surpasse l’état de l’art des systèmes, hybride ou pleine bande, dans la reconstruction de la parole, offrant une qualité transparente confirmé par des évaluations objectives et subjectives. En ce qui concerne les applications, le eaQHM et l’ aHM sont appliquées sur les modifications de la parole (de temps et pas mise à l’échelle). Les modifications qui en résultent sont de haute qualité, et suivent des règles très simples, par rapport à d’autres systèmes de modification état de l’art. Les résultats montrent que harmonicité est préféré au quasi- harmonicité de modifications de la parole du fait de la simplicité de la représentation intégrée. En outre, la pleine bande eaQHM est appliquée sur le problème de la modélisation des signaux audio, et en particulier d’instrument de musique retentit. Le eaQHM est évaluée et comparée à des systèmes à la pointe de la technologie, et leur est montré surpasser en termes de qualité de resynthèse, représentant avec succès l’attaque , transitoire, et une partie stationnaire d’un son d’instruments de musique. Enfin, une autre application est suggéré, à savoir l’analyse et la classification des discours émouvant. Le eaQHM est appliqué sur l’analyse des discours émouvant, offrant à ses paramètres instantanés comme des caractéristiques qui peuvent être utilisés dans la reconnaissance et la quantification vectorielle à base classification du contenu émotionnel de la parole. Bien que les modèles sinusoidaux sont pas couramment utilisés dans ces tâches, les résultats sont prometteurs. / Sinusoidal Modeling is one of the most widely used parametric methods for speech and audio signal processing. The accurate estimation of sinusoidal parameters (amplitudes, frequencies, and phases) is a critical task for close representation of the analyzed signal. In this thesis, based on recent advances in sinusoidal analysis, we propose high resolution adaptive sinusoidal models for analysis, synthesis, and modifications systems of speech. Our goal is to provide systems that represent speech in a highly accurate and compact way. Inspired by the recently introduced adaptive Quasi-Harmonic Model (aQHM) and adaptive Harmonic Model (aHM), we overview the theory of adaptive Sinusoidal Modeling and we propose a model named the extended adaptive Quasi-Harmonic Model (eaQHM), which is a non-parametric model able to adjust the instantaneous amplitudes and phases of its basis functions to the underlying time-varying characteristics of the speech signal, thus significantly alleviating the so-called local stationarity hypothesis. The eaQHM is shown to outperform aQHM in analysis and resynthesis of voiced speech. Based on the eaQHM, a hybrid analysis/synthesis system of speech is presented (eaQHNM), along with a hybrid version of the aHM (aHNM). Moreover, we present motivation for a full-band representation of speech using the eaQHM, that is, representing all parts of speech as high resolution AM-FM sinusoids. Experiments show that adaptation and quasi-harmonicity is sufficient to provide transparent quality in unvoiced speech resynthesis. The full-band eaQHM analysis and synthesis system is presented next, which outperforms state-of-the-art systems, hybrid or full-band, in speech reconstruction, providing transparent quality confirmed by objective and subjective evaluations. Regarding applications, the eaQHM and the aHM are applied on speech modifications (time and pitch scaling). The resulting modifications are of high quality, and follow very simple rules, compared to other state-of-the-art modification systems. Results show that harmonicity is preferred over quasi-harmonicity in speech modifications due to the embedded simplicity of representation. Moreover, the full-band eaQHM is applied on the problem of modeling audio signals, and specifically of musical instrument sounds. The eaQHM is evaluated and compared to state-of-the-art systems, and is shown to outperform them in terms of resynthesis quality, successfully representing the attack, transient, and stationary part of a musical instrument sound. Finally, another application is suggested, namely the analysis and classification of emotional speech. The eaQHM is applied on the analysis of emotional speech, providing its instantaneous parameters as features that can be used in recognition and Vector-Quantization-based classification of the emotional content of speech. Although the sinusoidal models are not commonly used in such tasks, results are promising.

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Στην παρούσα διπλωματική εργασία γίνεται μελέτη της ανάλυσης και σύνθεσης ήχου με τη βοήθεια ημιτονοειδών. Ειδικότερα, εξετάζονται οι παράμετροι της ανάλυσης και σύνθεσης και πως αυτες επηρεάζουν την τελική ανακατασκευή του σήματος. Στη συνέχεια γίνεται διερεύνηση της ανάλυσης και σύνθεσης μόνο στις χαμηλές συχνότητες. Με βάση ένα περιορισμένο εύρος ζώνης, γίνεται ανίχνευση των τονικών υψών. Αναπτύσσονται τρεις μέθοδοι κατηγοριοποίησης τους και στη συνέχεια γίνεται μία αξιολόγηση των μεθόδων αυτών μέσω των μέτρων NMR και PEAQ. / In this degree thesis sound analysis and synthesis using sinusoidals is studied. More specifically, parameters of analysis and synthesis are examined and how they affect the final reconstruction of a signal. Further research is conducted for analysis and synthesis at low sound frequencies. Based on a limited bandwidth, pitch detection is taking place on the input signal. Three methods of categorizing frequencies are developed and they are evaluated using the metrics of NMR (Noise to Mask Ratio) and PEAQ (Perceptual Evaluation of Audio Quality).

This diploma thesis deals with the theoretical analysis of the predictive methods of signal interpolation and signal modeling using sinusoidal model. On the basis of this theory the algorithm for the reconstruction of the missing sections in the audio signal is implemented in computing environment MATLAB. Results of mass testing reconstructions are displayed using objective methods SNR and PEMO-Q. Further experiments are carried out on single signals and their evaluation is described.

Sound Source Separation refers to separating sound signals according to their sources from a given observed sound. It is efficient to code and very easy to analyze and manipulate sounds from individual sources separately than in a mixture. This thesis deals with the problem of source separation in monaural recordings of harmonic musical instruments. A good amount of literature is surveyed and presented since sound source separation has been tried by many researchers over many decades through various approaches. A prediction driven approach is first presented which is inspired by old-plus-new heuristic used by humans for Auditory Scene Analysis. In this approach, the signals from different sources are predicted using a general model and then these predictions are reconciled with observed sound to get the separated signal. This approach failed for real world sound recordings in which the spectrum of the source signals change very dynamically. Considering the dynamic nature of the spectrums, an approach which uses covariance matrix of amplitudes of harmonics is proposed. The overlapping and non-overlapping harmonics of the notes are first identified with the knowledge of pitch of the notes. The notes are matched on the basis of their covariance profiles. The second order properties of overlapping harmonics of a note are estimated with the use of co-variance matrix of a matching note. The full harmonic is then reconstructed using these second order characteristics. The technique has performed well over sound samples taken from RWC musical Instrument database.