This paper proposes near-field sound-source localization based on crosscorrelation of a signed binary code. The signed binary code eliminates multibit signal processing for simpler implementation. Explicit formulae with near-field assumption are derived for a two microphone scenario and extended to a three microphone case with front-rear discrimination. Adaptive threshold for enabling and disabling source localization is developed for robustness in noisy environment. The proposed sound-source localization algorithm is implemented on a fixed-point DSP. Evaluation results in a robot scenario demonstrate that near-field assumption and front-rear discrimination provides almost 40% improvement in DOA estimation. A correct detection rate of 85% is obtained by a robot in a home environment.

This paper proposes a new echo suppressor based on spectral correlation between the residual echo and the echo replica in an ordinary echo canceller. First, it is revealed by experiments that there is a significant correlation between the spectral amplitudes of the residual echo and the echo replica, and a new model for nonlinear-echo suppression based on the correlation is derived. Next, a new echo suppressor controlling the gain in each frequency bin to suppress the residual echo based on the new model is developed. Simulation results with speech data recorded by a hands-free cellphone show that the proposed echo suppressor reduces the residual echo to an almost inaudible level.

This paper proposes a new adaptation-mode control (AMC) for a robust adaptive microphone array with an adaptive blocking matrix (RAMA-ABM). The proposed AMC is based on cross correlations of two microphone signals and uses a state machine for controlling the adaptation to avoid target-signal cancellation. Evaluation with sound data obtained in different acoustic environments demonstrates that the noise reduction by the proposed AMC is 3 dB better than that by the AMC based on the SNR estimate. Subjective listening tests show that the quality of the output signal by the proposed AMC is comparable to or even better than those by the conventional AMCs.

This paper proposes a new robust adaptive beamformer applicable to microphone arrays. The proposed beamformer is a generalized sidelobe canceller (GSC) with a variable blocking matrix using coefficient-constrained adaptive filters (CCAFs). The CCAFs, whose common input signal is the output of a fixed beamformer, minimize leakage of the target signal into the interference path of the GSC. Each coefficient of the CCAFs is constrained to avoid mistracking. In the multiple-input canceller, leaky adaptive filters are used to decrease undesirable target-signal cancellation. The proposed beamformer can allow large look-direction error with almost no degradation in interference-reduction performance and can be implemented with a small number of microphones. The maximum allowable look-direction error can be specified by the user. Simulation results show that the proposed beamformer, when designed to allow about 20of look-direction error, can suppress interference by more than 17 dB.