This book addresses the problem of separating spontaneous multi-party speech by way of microphone arrays (beamformers) and adaptive signal processing techniques. It is written is a concise manner and an effort has been made such that all presented algorithms can be straightforwardly implemented by the reader. All experimental results have been obtained with real in-car microphone recordings involving simultaneous speech of the driver and the co-driver.
Time-Domain Beamforming and Blind Source Separation
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This book addresses the problem of separating spontaneous multi-party speech by way of microphone arrays (beamformers) and adaptive signal processing techniques. It is written is a concise manner and an effort has been made such that all presented algorithms can be straightforwardly implemented by the reader. All experimental results have been obtained with real in-car microphone recordings involving simultaneous speech of the driver and the co-driver.
A systematic exploration of both classic and contemporary algorithms in blind source separation with practical case studies The book presents an overview of Blind Source Separation,...
ICA and its variations are used extensively in BSS. Most of the algorithms that are used to separate speech or music signals utilize ICA in the time frequency domain. Here ICA is applied in the...
This book is presenting the beamforming techniques for speech separation using microphone arrays. The primary aim of the project is to increase the speech recognition accuracy by minimising the...
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