Christophe Couvreur

Christophe Couvreur
research category image

Main area of research
Speech recognition

Christophe Couvreur is Vice-President & General Manager, TTS Business Line at Nuance Communications, Inc. where he is in charge of the Vocalizer family of speech synthesis technologies. He has been with Nuance Communications since 2001 in a variety of positions in research, engineering, project management and program management, all focused on bringing innovative speech products to market in the Automotive, Mobile or Gaming area. His technical interests span the full range of Nuance technologies, from speech recognition and speech enhancement to speech synthesis and user interaction. Prior to Nuance, Christophe worked as a researcher at Lernout & Hauspie Speech Products, the University of Illinois at Urbana-Champaign and the Belgian National Fund for Scientific Research. He has also served as a Lieutenant in the Belgian Air Force. Christophe holds a PhD in Applied Science from Faculté Polytechnique Mons (Belgium), a Master degree in Electrical Engineering from the University of Illinois at Urbana-Champaign, a Master degree in Mathematics from Université Catholique de Louvain (UCL), as well as a MBA from Vlerick Business School.

Selected articles

Doppler-Based Movement Estimation for Wide Band Sources From Single Sensor Measurements

We address the problem of estimating the motion of a wide-band source from single passive sensor measurements, for example, estimation of the speed and position

Read more

Model-based Feature Enhancement for Noisy Speech Recognition

In this paper, a new feature enhancement algorithm called model-based feature enhancement (MBFE) is introduced for noise robust speech recognition. In MBFE, statistical models (i.e.,

Read more

Database Adaptation for ASR in Cross-Environmental Conditions in the SPEECON Project

As part of the SPEECON corpora collection project, a software toolbox for transforming speech recordings made in a quiet environment with a close-talk microphone into

Read more

The EM Algorithm: A Guided Tour

The Expectation-Maximization (EM) algorithm has become one of the methods of choice for maximum-likelihood (ML) estimation. In this tutorial paper, the basic principles of the

Read more

Automatic Classification of Environmental Noise Events by Hidden Markov Models

The automatic classification of environmental noise sources from their acoustic signatures recorded at the microphone of a noise monitoring system (NMS) is an active subject

Read more


1 2 3