Some Contributions to Music Signal Processing and to Mono-Microphone Blind Audio Source Separation (2010)
Abstract / truncated to 115 words
For humans, the sound is valuable mostly for its meaning. The voice is spoken language, music, artistic intent. Its physiological functioning is highly developed, as well as our understanding of the underlying process. It is a challenge to replicate this analysis using a computer: in many aspects, its capabilities do not match those of human beings when it comes to speech or instruments music recognition from the sound, to name a few. In this thesis, two problems are investigated: the source separation and the musical processing. The first part investigates the source separation using only one Microphone. The problem of sources separation arises when several audio sources are present at the same moment, mixed together ... toggle 5 keywordssource separation – autoregressive model – ornementation – adaptive filtering – spectral analysis
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