Tracking and separation of multiple moving speech sources via cardinality balanced multi-Target multi Bernoulli (CBMeMBer) filter and time frequency masking
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In a 'conference room scenario', the number of speech sources are not known a priori and the number of speech sources which are active remains unknown as these speech sources appear and disappear throughout the measurement period. Furthermore, the speech sources are moving so their mixing parameters change with time. As a result of this, traditional source separation techniques are limited by their capability to properly attribute the correct mixing parameters to the respective sources. The 'conference room scenario' problem is very challenging as it involves the localization, tracking and separation of a time varying number of moving speech sources. An online solution which systematically solves 'conference room scenario' problem by solving the source localization, tracking and separation in stages is proposed in this paper.
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Source separation employing beamforming and SRP-PHAT localization in three-speaker room environmentsNordholm, Sven (2017)This paper presents a new blind speech separation algorithm using beamforming technique that is capable of extracting each individual speech signal from a mixture of three speech sources in a room. The speech separation ...
Chong, Nicholas Ewe Hai (2015)The problem of separating a time varying number of speech sources in a room is difficult to solve. The challenge lies in estimating the number and the location of these speech sources. Furthermore, the tracked speech ...
Dam, H.; Nordholm, Sven (2013)This paper investigates the problem of subband speech separation from a mixture of two speech signals in a room environment. Due to the lack of source information, a sound source localization is proposed for beamformer ...