Application of Blind Signal Separation in Speech Processing
نویسندگان
چکیده
منابع مشابه
Beamspace blind signal separation for speech enhancement
Signal processing methods for speech enhancement are of vital interest for communications equipments. In particular, multichannel algorithms, which perform spatial filtering to separate signals that have overlapping frequency content but different spatial origins, are important for a wide range of applications. Two of the most popular multichannel methods are blind signal separation (BSS) and b...
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Blind Source Separation (BSS) is a statistical approach to separating individual signals from an observed mixture of a group of signals. BSS relies on only very weak assumptions on the signals and the mixing process (hence the “blind” descriptor) and this blindness enables the technique to be used in a wide variety of situations. Research in the field of Blind Source Separation has resulted in ...
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Blind signal separation method based on minimizing mutual information is applied to deal with multispeaker problem in speech recognition. Recognition experiments performed under di erent acoustic environments, in a soundproof room and a reverberant room, clarify that 1) the method can improve recognition accuracy by about 20% where SNR condition is 0 dB, 2) the method is more e ective when many...
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Blind Signal Separation (BSS) techniques are commonly employed in the separation of speech signals, using Independent Component Analysis (ICA) as the criterion for separation. This paper investigates the viability of employing ICA for real-time speech separation (where short frame sizes are the norm). The relationship between the statistics of speech and the assumption of statistical independen...
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ژورنال
عنوان ژورنال: Energy Procedia
سال: 2011
ISSN: 1876-6102
DOI: 10.1016/j.egypro.2011.11.549