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2 results on '"Laurent Girin"'

1. Adaptive Long-Term Coding of LSF Parameters Trajectories for Large-Delay/Very- to Ultra-Low Bit-Rate Speech Coding

Author

Laurent Girin

Subjects
Acoustics. Sound, QC221-246, Electronic computers. Computer science, QA75.5-76.95
Abstract

This paper presents a model-based method for coding the LSF parameters of LPC speech coders on a “long-term” basis, that is, beyond the usual 20–30 ms frame duration. The objective is to provide efficient LSF quantization for a speech coder with large delay but very- to ultra-low bit-rate (i.e., below 1 kb/s). To do this, speech is first segmented into voiced/unvoiced segments. A Discrete Cosine model of the time trajectory of the LSF vectors is then applied to each segment to capture the LSF interframe correlation over the whole segment. Bi-directional transformation from the model coefficients to a reduced set of LSF vectors enables both efficient “sparse” coding (using here multistage vector quantizers) and the generation of interpolated LSF vectors at the decoder. The proposed method provides up to 50% gain in bit-rate over frame-by-frame quantization while preserving signal quality and competes favorably with 2D-transform coding for the lower range of tested bit rates. Moreover, the implicit time-interpolation nature of the long-term coding process provides this technique a high potential for use in speech synthesis systems.

Published
2010
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2. Separation of Audio-Visual Speech Sources: A New Approach Exploiting the Audio-Visual Coherence of Speech Stimuli

Author

Laurent Girin, David Sodoyer, Christian Jutten, Jacob Klinkisch, and Jean-Luc Schwartz

Subjects
Audio mining, Computer science, audio-visual speech processing, Speech recognition, Speech coding, lcsh:Electronics, Acoustic model, lcsh:TK7800-8360, Coherence (statistics), Speech processing, Blind signal separation, lcsh:Telecommunication, lipreading, Hardware and Architecture, blind source separation, lcsh:TK5101-6720, Signal Processing, Source separation, Electrical and Electronic Engineering, Independence (probability theory)
Abstract

We present a new approach to the source separation problem in the case of multiple speech signals. The method is based on the use of automatic lipreading, the objective is to extract an acoustic speech signal from other acoustic signals by exploiting its coherence with the speaker′s lip movements. We consider the case of an additive stationary mixture of decorrelated sources, with no further assumptions on independence or non-Gaussian character. Firstly, we present a theoretical framework showing that it is indeed possible to separate a source when some of its spectral characteristics are provided to the system. Then we address the case of audio-visual sources. We show how, if a statistical model of the joint probability of visual and spectral audio input is learnt to quantify the audio-visual coherence, separation can be achieved by maximizing this probability. Finally, we present a number of separation results on a corpus of vowel-plosive-vowel sequences uttered by a single speaker, embedded in a mixture of other voices. We show that separation can be quite good for mixtures of 2, 3, and 5 sources. These results, while very preliminary, are encouraging, and are discussed in respect to their potential complementarity with traditional pure audio separation or enhancement techniques.

Published
2002

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