Fundamentals of speech recognition
Fundamentals of speech recognition
Independent component analysis, a new concept?
Signal Processing - Special issue on higher order statistics
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97)-Volume 2 - Volume 2
Microphone Array Based Speech Recognition with Different Talker-Array Positions
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Broadband Beamforming with Adaptive Postfiltering for Speech Acquisition in Noisy Environments
ICASSP '97 Proceedings of the 1997 IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP '97) -Volume 1 - Volume 1
Speech enhancement using microphone array
Speech enhancement using microphone array
Visualizing the performance of large-aperture microphone arrays
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Blind source separation combining independent component analysis and beamforming
EURASIP Journal on Applied Signal Processing
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
ICASSP '09 Proceedings of the 2009 IEEE International Conference on Acoustics, Speech and Signal Processing
Blind Spatial Subtraction Array for Speech Enhancement in Noisy Environment
IEEE Transactions on Audio, Speech, and Language Processing
Microphone array speech processing
EURASIP Journal on Advances in Signal Processing - Special issue on microphone array speech processing
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We conduct an objective analysis on musical noise generated by two methods of integrating microphone array signal processing and spectral subtraction. To obtain better noise reduction, methods of integrating microphone array signal processing and nonlinear signal processing have been researched. However, nonlinear signal processing often generates musical noise. Since such musical noise causes discomfort to users, it is desirable that musical noise is mitigated. Moreover, it has been recently reported that higherorder statistics are strongly related to the amount of musical noise generated. This implies that it is possible to optimize the integration method from the viewpoint of not only noise reduction performance but also the amount of musical noise generated. Thus, we analyze the simplest methods of integration, that is, the delay-and-sum beamformer and spectral subtraction, and fully clarify the features of musical noise generated by each method. As a result, it is clarified that a specific structure of integration is preferable from the viewpoint of the amount of generated musical noise. The validity of the analysis is shown via a computer simulation and a subjective evaluation.