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In this paper, we address the issue of underdetermined source separation of I nonstationary audio sources from a J -channel linear instantaneous mixture (J <; I). This problem is addressed with a specific coder-decoder configuration. At the coder, source signals are assumed to be available before the mixing is processed. A time-frequency (TF) joint analysis of each source signal and mixture signal...
In this paper, we address the issue of audio source separation with a single channel, i.e. the estimation of source signals from a single mixture of these signals. This problem is addressed with a specific configuration: source signals are assumed to be available before the mix is processed. We propose an original method that uses a watermarking technique to embed information about the source signals...
We present a new algorithm for the automatic estimation of the voicing cut-off frequency (VCO), i.e., the frequency that separates the periodic low-frequency part from the aperiodic high-frequency part in voiced segments of natural speech. Starting from the power spectrum of a two pitch period speech frame, we define the VCO to be located at the frequency for which the sum of the periodic and aperiodic...
This paper presents a method for modeling the envelope of spectral amplitude parameters of speech signals in "two dimensions" (2D). It consists of two cascaded modelings: the first one along the frequency axis is the usual cepstrum technique, which consists of modeling the log-scaled spectral envelope with a discrete cosine model (DCM). The second one, along the time axis, consists of modeling...
Audio-visual speech source separation consists in mixing visual speech processing techniques (e.g. lip parameters tracking) with source separation methods to improve and/or simplify the extraction of a speech signal from a mixture of acoustic signals. In this paper, we present a new approach to this problem: visual information is used here as a voice activity detector (VAD). Results show that, in...
We present a new approach to the voice activity detection (VAD) problem for speech signals embedded in non-stationary noise. The method is based on automatic lipreading: the objective is to detect voice activity or non-activity by exploiting the coherence between the speech acoustic signal and the speaker's lip movements. From a comprehensive analysis of lip shape parameters during speech and non-speech...
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