Pierre Lanchantin
ATIAM 2000-2001
• My research area is statistical signal processing. My main topics of research include statistical modeling of signals, speech processing and their applications to Music.
• My research has focused initially on the generalization of statistical models for signals, especially Hidden Markov Models (HMM). During my PhD, I studied models called Triplet Markov models that generalize the classical HMM with applications in image segmentation.
• I then directed my research toward speech processing and joined the analysis/synthesis team at IRCAM, working on the segmentation of speech signals into phones, voice conversion, language models and HMM-based speech synthesis.
• I finally joined the Speech Research Group of the Cambridge University Engineering Department (CUED) where I will develop core learning and adaptation techniques for the Natural Speech Technology (NST) project
• My research studies on speech are interdisciplinary as they combine statistical modeling of signals, natural language processing and their application to music.
Specialties
• Hidden Markov Models (HMM) for Image and Speech processing
• HMM-based Speech synthesis (HTS)
• Voice Conversion
• Speech recognition
• Signal and Image Segmentation
• Data fusion
Site web : http://recherche.ircam.fr/equipes/analyse-synthese/lanchant/