Auditory System for a Mobile Robot
Jean-Marc Valin

TL;DR
This thesis presents an artificial auditory system for mobile robots capable of localizing, tracking, separating, and recognizing multiple sound sources in noisy environments, enhancing human-robot interaction.
Contribution
It introduces a non-human-inspired microphone array system with integrated algorithms for sound source localization, tracking, separation, and speech recognition, demonstrating real-time multi-source processing.
Findings
Tracks up to four sound sources in noisy, reverberant environments
Achieves 13.7 dB SNR improvement with three speakers
Over 80% digit recognition accuracy in tested scenarios
Abstract
In this thesis, we propose an artificial auditory system that gives a robot the ability to locate and track sounds, as well as to separate simultaneous sound sources and recognising simultaneous speech. We demonstrate that it is possible to implement these capabilities using an array of microphones, without trying to imitate the human auditory system. The sound source localisation and tracking algorithm uses a steered beamformer to locate sources, which are then tracked using a multi-source particle filter. Separation of simultaneous sound sources is achieved using a variant of the Geometric Source Separation (GSS) algorithm, combined with a multi-source post-filter that further reduces noise, interference and reverberation. Speech recognition is performed on separated sources, either directly or by using Missing Feature Theory (MFT) to estimate the reliability of the speech features.…
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Taxonomy
TopicsSpeech and Audio Processing · Blind Source Separation Techniques · Advanced Adaptive Filtering Techniques
