In modern devices which provide hands-free speech capturing functionality, such as hands-free communication kits and voice-controlled devices, the received speech signal at the microphones is corrupted by background noise, interfering speech signals, and room reverberation. In many practical situations, the microphones are not necessarily located near the desired source, and hence, the ratio of the desired speech power to the power of the background noise, the interfering speech, and the reverberation at the microphones can be very low, often around or even below 0 dB. In such situations, the comfort of human-to-human communication, as well as the accuracy of automatic speech recognisers for voice-controlled applications can be significantly degraded. Therefore, e↵ective speech enhancement algorithms are required to process the microphone signals before transmitting them to the far-end side for communication, or before feeding them into a speech recognition engine. This thesis is concerned with multi-microphone speech enhancement in reverberant environments, in the presence of background noise and non-stationary interferers, such as interfering speakers. The desired speech signal that needs to be enhanced is usually application-dependent and can originate from one or multiple speakers. The background noise and the non-stationary interferers, constitute undesired signals. Specific tasks of interest in this thesis are undesired signal reduction, Blind Source Separation (BSS), and acoustic source detection and tracking. While single-channel speech enhancement and noise reduction have been extensively studied for more than four decades, efficient solutions to challenging problems such as BSS, acoustic source tracking, and speech enhancement in scenarios with multiple speech sources, have emerged more recently as a result of the rapid development in multi-channel speech processing and the availability of multiple microphones in commercial products, e.g., mobile phones, laptops, smart watches, hearing aids, etc. The ...
Informed spatial filters for speech enhancement: Noise and Interference Reduction, Blind Source Separation, and Acoustic Source Tracking ; Informed spatial filters für Sprachsignalverbesserung: Rauschunterdrückung, Quellentrennung, und Verfolgung von akustischen Quellen
2018-01-01
Hochschulschrift
Elektronische Ressource
Englisch
DDC: | 629 |
A Performance Assessment on Rotor Noise-Informed Active Multidrone Sound Source Tracking Methods
DOAJ | 2024
|Coordinated Views for Informed Spatial Decision Making
British Library Conference Proceedings | 2003
|Coordinated views for informed spatial decision making
IEEE | 2003
|