Zbyněk Koldovský, J. Málek, P. Tichavský, F. Nesta
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Semi-Blind Noise Extraction Using Partially Known Position of the Target Source
An extracted noise signal provides important information for subsequent enhancement of a target signal. When the target's position is fixed, the noise extractor could be a target-cancellation filter derived in a noise-free situation. In this paper we consider a situation when such cancellation filters are prepared for a set of several possible positions of the target in advance. The set of filters is interpreted as prior information available for the noise extraction when the target's exact position is unknown. Our novel method looks for a linear combination of the prepared filters via Independent Component Analysis. The method yields a filter that has a better cancellation performance than the individual filters or filters based on a minimum variance principle. The method is tested in a highly noisy and reverberant real-world environment with moving target source and interferers. A post-processing by Wiener filter using the noise signal extracted by the method is able to improve signal-to-noise ratio of the target by up to 8 dB.
期刊介绍:
The IEEE Transactions on Audio, Speech and Language Processing covers the sciences, technologies and applications relating to the analysis, coding, enhancement, recognition and synthesis of audio, music, speech and language. In particular, audio processing also covers auditory modeling, acoustic modeling and source separation. Speech processing also covers speech production and perception, adaptation, lexical modeling and speaker recognition. Language processing also covers spoken language understanding, translation, summarization, mining, general language modeling, as well as spoken dialog systems.