Open AccessJournal Article
Speech Enhancement Using Nonlinear Microphone Array Based on Complementary Beamforming
Reads0
Chats0
TLDR
In this article, a spatial spectral subtraction method by using the complementary beamforming microphone array to enhance noisy speech signals for speech recognition is described, which is based on two types of beamformers designed to obtain complementary directivity patterns with respect to each other.Abstract:
This paper describes a spatial spectral subtraction method by using the complementary beamforming microphone array to enhance noisy speech signals for speech recognition. The complementary beamforming is based on two types of beamformers designed to obtain complementary directivity patterns with respect to each other. In this paper, it is shown that the nonlinear subtraction processing with complementary beamforming can result in a kind of the spectral subtraction without the need for speech pause detection. In addition, the optimization algorithm for the directivity pattern is also described. To evaluate the effectiveness, speech enhancement experiments and speech recognition experiments are performed based on computer simulations under both stationary and nonstationary noise conditions. In comparison with the optimized conventional delayand-sum (DS) array, it is shown that: (1) the proposed array improves the signal-to-noise ratio (SNR) of degraded speech by about 2 dB and performs more than 20% better in word recognition rates under the conditions that the white Gaussian noise with the input SNR of −5 or −10 dB is used, (2) the proposed array performs more than 5% better in word recognition rates under the nonstationary noise conditions. Also, it is shown that these improvements of the proposed array are same as or superior to those of the conventional spectral subtraction method cascaded with the DS array. key words: speech enhancement, microphone array, complementary beamforming, spectral subtraction, speech recognitionread more
Citations
More filters
Proceedings Article
Real-time sound source localization and separation for robot audition
TL;DR: The active direction-pass filter (ADPF) to separate sounds originating from the specified direction with a pair of microphones is presented and the signal-to-noise ratio (SNR) of each sound separated from a mixture of two speeches with the same loudness is improved.
Journal ArticleDOI
Improvement of recognition of simultaneous speech signals using AV integration and scattering theory for humanoid robots
TL;DR: A method to improve recognition of three simultaneous speech signals by a humanoid robot equipped with a pair of microphones by using two key ideas: two-layered audio–visual integration of both name and location and acoustical modeling of the humanoid head by scattering theory.
Journal ArticleDOI
Underdetermined Sound Source Separation Using Power Spectrum Density Estimated by Combination of Directivity Gain
TL;DR: Simulation results proved that the proposed method effectively separated up to M(M-1)+1 sound sources if the fixed beamformers were appropriately selected, and was also effective in practical use.
Book ChapterDOI
Nonlinear speech enhancement: an overview
TL;DR: An overview of the main classes of noise reduction algorithms proposed to-date, focusing on the case of additive independent noise, and the impact of nonlinearity on the speech enhancement problem is highlighted.
Proceedings ArticleDOI
Circular microphone array for robot's audition
TL;DR: In this article, a 32-channel circular microphone array is used to localize individual sounds from many sound sources in 360 degrees, which can be used in robot audition and is evaluated by a sound pressure distribution map.