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The goal of this thesis is to develop and design new feature representations that can improve the automatic speech recognition (ASR) performance in clean as well noisy conditions. One of the main shortcomings of the fixed scale (typically 20-30 ms long ana ...
We investigate how the sound field induced by an acoustic event evolves over space and time. The characteristics of its bidimensional Fourier spectrum are analyzed and spatio-temporal sampling results using an array of microphones are provided for differen ...
The massive amount of data recorded by dense electrode arrays which are routinely connected to Nyquist-sampling signal conditioning blocks introduces new design challenges for implantable and wireless biological signal acquisition. Five different architect ...
This paper introduces a novel approach for extracting speaker embeddings from audio mixtures of multiple overlapping voices. This approach is based on a multi-task neural network. The network first extracts a latent feature for each direction. This feature ...
In this paper, a probabilistic measure for reliability of speaker verification under noisy acoustic conditions is proposed. A Bayesian network is used to estimate a probability for verification errors, given the GMM-based speaker verification system output ...
In this paper, a probabilistic measure for reliability of speaker verification under noisy acoustic conditions is proposed. A Bayesian network is used to estimate a probability for verification errors, given the GMM-based speaker verification system output ...
The aim of this work was to analyze the global behavior of a loudspeaker exciting a room in the frequency band of its first modes, for the purpose of active control applications. First, the loudspeaker in free field was studied. The characterization of a l ...
