Author ORCID Identifier
Date Available
4-28-2017
Year of Publication
2017
Degree Name
Master of Science in Electrical Engineering (MSEE)
Document Type
Master's Thesis
College
Engineering
Department/School/Program
Electrical and Computer Engineering
First Advisor
Dr. Kevin D. Donohue
Abstract
Time-Frequency (TF) masking is an audio processing technique useful for isolating an audio source from interfering sources. TF masking has been applied and studied in monaural and binaural applications, but has only recently been applied to distributed microphone arrays. This work focuses on evaluating the TF masking technique's ability to isolate human speech and improve speech intelligibility in an immersive "cocktail party" environment. In particular, an upper-bound on TF masking performance is established and compared to the traditional delay-sum and general sidelobe canceler (GSC) beamformers. Additionally, the novel technique of combining the GSC with TF masking is investigated and its performance evaluated. This work presents a resource-efficient method for studying the performance of these isolation techniques and evaluates their performance using both virtually simulated data and data recorded in a real-life acoustical environment. Further, methods are presented to analyze speech intelligibility post-processing, and automated objective intelligibility measurements are applied alongside informal subjective assessments to evaluate the performance of these processing techniques. Finally, the causes for subjective/objective intelligibility measurement disagreements are discussed, and it was shown that TF masking did enhance intelligibility beyond delay-sum beamforming and that the utilization of adaptive beamforming can be beneficial.
Digital Object Identifier (DOI)
https://doi.org/10.13023/ETD.2017.145
Recommended Citation
Morgan, Joshua P., "Time-Frequency Masking Performance for Improved Intelligibility with Microphone Arrays" (2017). Theses and Dissertations--Electrical and Computer Engineering. 101.
https://uknowledge.uky.edu/ece_etds/101