Source Localization for Dual Speech Enhancement Technology

Abstract

Many researchers have investigated multi-channel speech enhancement techniques which can be used for the pre-processing of the speech recognition system. Numerous microphones can give high performance, but they require additional hardware costs and generate the design problem about microphone position. Therefore speech enhancement technique using two microphones is preferred in mobile phone such as LG KM900, iPhone 4 and Nexus One. For enhancing the speech with two or more microphones, the spatial information from the input signal's incident angle should be used. Therefore, various sound source localization(SSL) methods have been used to estimate the talker’s direction-ofarrival(DOA). There are two main approaches to localization (Brandstein, 1995), (Dibase, 2000): the steered-beamformer approach, which includes various kinds of beamformers; and time-difference of arrival (TDOA) approach, which includes a generalized cross-correlation (GCC). The steered-beamformer approach has the capability of enhancing a desired signal that originates from a particular direction. The beamformer can steer its response at a particular angle; it can then find the spatial information required to maximize the beamformer output by scanning over a predefined spatial region. For this purpose, we can use a simple conventional delay-and-sum beamformer or many optimum beamfomers (Naguib, 1996). The TDOA approach uses classical time delay estimation techniques, such as cross-correlation, GCC, adaptive time delay estimation, and the adaptive eigenvalue decomposition algorithm (Chen et al., 2006). The most common time delay estimation method is the GCC, which consists of various types such as the unfiltered type, the maximum likelihood (ML) type, and the phase transform (PHAT) type. The GCC-PHAT is a widely used for TDOA estimation method because it works well in a realistic environment. The resolution of the DOA estimator is deeply related to the aperture size of the array and the number of microphone. A large aperture size and microphones make an accurate estimation result. Therefore, SSL method using two microphones cannot give the accurate direction-of-arrival (DOA) estimation result. Moreover, the implementation of a TDOA estimator requires a voice activity detector (Araki et al., 2007) or a speech/non speech detector (Lathoud, 2006). However, the TDOA estimation often shows a failed result in spite of these kinds of additional processing. Hence, reliable SSL algorithm is needed for dual channel speech enhancement system.