Real-time Sound Source Separation For Music Applications

Sound source separation refers to the task of extracting individual sound sources from some number of mixtures of those sound sources. In this thesis, a novel sound source separation algorithm for musical applications is presented. It leverages the fact that the vast majority of commercially recorded music since the 1950s has been mixed down for two channel reproduction, more commonly known as stereo. The algorithm presented in Chapter 3 in this thesis requires no prior knowledge or learning and performs the task of separation based purely on azimuth discrimination within the stereo field. The algorithm exploits the use of the pan pot as a means to achieve image localisation within stereophonic recordings. As such, only an interaural intensity difference exists between left and right channels for a single source. We use gain scaling and phase cancellation techniques to expose frequency dependent nulls across the azimuth domain, from which source separation and resynthesis is carried out. The algorithm is demonstrated to be state of the art in the field of sound source separation but also to be a useful pre-process to other tasks such as music segmentation and surround sound upmixing

Modulation vocoder for analysis, processing and synthesis of audio signals with application to frequency selective pitch transposition

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Speech, time-frequency representations

This paper presents a review on the use of time frequency representations in the fields of speech analysis and automatic speech processing . Three main groups of methods are considered : speech production based methods, general signal analysis methods, auditory-based methods . After this review, some short conclusions on their carrent use, and on some possible future evolutions are proposed .Le propos de cet article est de présenter une bibliographie récente sur l'utilisation des méthodes de représentation temps-fréquence en analyse et en traitement automatique de la parole. Les méthodes sont classées en trois grandes familles: méthodes dérivées de la production, méthodes d'analyse du signal, méthodes modélisant la perception. Après ce panorama, quelques rapides conclusions sur l'état actuel de l'utilisation de ces méthodes, et quelques perspectives sont tentée

Principled methods for mixtures processing

This document is my thesis for getting the habilitation à diriger des recherches, which is the french diploma that is required to fully supervise Ph.D. students. It summarizes the research I did in the last 15 years and also provides the short­term research directions and applications I want to investigate. Regarding my past research, I first describe the work I did on probabilistic audio modeling, including the separation of Gaussian and α­stable stochastic processes. Then, I mention my work on deep learning applied to audio, which rapidly turned into a large effort for community service. Finally, I present my contributions in machine learning, with some works on hardware compressed sensing and probabilistic generative models.My research programme involves a theoretical part that revolves around probabilistic machine learning, and an applied part that concerns the processing of time series arising in both audio and life sciences

Real-time spectral modelling of audio for creative sound transformation

EThOS - Electronic Theses Online ServiceGBUnited Kingdo