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Generalizing DoA estimation across diverse microphone arrays could revolutionize audio processing in mobile and dynamic environments.
A training-free dynamic clustering method significantly improves long speech separation performance, especially in sparse scenarios with unknown speaker counts.
Greedy selection of segments based on gradient embeddings can dramatically improve rare call-type classification in bioacoustics, achieving superior performance over traditional methods.
Achieving a mean angular error of just 11.3 degrees in head orientation estimation could revolutionize applications in smart environments and driver monitoring.
