Many optimal steered beamformer techniques have been derived for stationary

Many optimal steered beamformer techniques have been

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Many optimal steered-beamformer techniques have been derived for stationary, narrow-band signals. These include minimum variance beamforming [58][26][66], linear prediction [58] and generalize sidelobe cancellers [44][16]. These methods can be extended to the wideband case and are appropriate for speech signals when applied over short, stationary segments. However, the beamformer filters for all of these methods are defined in terms of the spatial correlation matrix . When this matrix is unknown, it must be estimated using the observed data. Such estimation, especially in adverse acoustic conditions, may require long segments of stationary data. For the dynamic conditions of speech-array applications, long interval for which the source is both spatial and temporally stationary are rarely encountered. Hence, such methods are difficult to apply to the localization of speech sources. In this thesis, filters for a steered-beamformer are derived, which incorporate the features of a popular pairwise technique known as the phase transform (PHAT). The phase transform is a sub-optimal method, although it has been shown to perform well in reverberant environments. In this thesis, it will be demonstrated that this new steered-beamformer produces highly reliable location estimates, in rooms with reverberation times of 200 and 400 milliseconds, using 25-millisecond data segments. It is compared to the conventional form of steered-beamformer localization and to a pairwise technique based on the phase transform. Using unique microphone array data sets, recorded in realistic environments, the new technique is demonstrated to be more robust to reverberation than the other two methods. 1.3 This Thesis This thesis attempts to show that pairwise localization techniques yield inadequate performance in some realistic small-room environments. Unique array data sets were collected using specially designed microphone array-systems. Through the used of this data, various localization methods were analyzed and compared. These methods are based on both the generalized cross-correlation (GCC) and the steered response power (SRP). The GCC techniques studied include the phase transform, which has been dubbed “GCC-PHAT”. The beam-steering methods are based on the conventional steered response power (SRP) 6
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and a new filter-and-sum technique dubbed “SRP-PHAT”. The goals of this work can be summarized as follows: To show that mild reverberation can severely impact the performance of short-time GCC-based localization techniques To show that microphone redundancy, which exists in many array systems, can be exploited to reduce the data requirements for accurate talker localization in reverberant environments To examine the performance of steered-response localization techniques when applied to realistic speech-array data sets To propose a new steered-beamformer localization method, SRP-PHAT, that is more accurate than both the conventional method and the popular pairwise method, GCC-PHAT.
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