Method for sound source direction estimation based on time frequency masking and deep neural network

A deep neural network, time-frequency masking technology, applied in systems for determining direction or offset, direction finders using ultrasonic/sonic/infrasonic waves, etc., can solve problems such as poor robustness and improve accuracy and stability. , strong and robust effect

Active Publication Date: 2019-06-04
ELEVOC TECH CO LTD
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Problems solved by technology

[0004] In order to solve the technical problem of poor robustness of orientation estimation, the present disclosure provides a sound source direction estimation method, device, electronic equipment, and storage medium based on time-frequency masking and deep neural network

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  • Method for sound source direction estimation based on time frequency masking and deep neural network
  • Method for sound source direction estimation based on time frequency masking and deep neural network
  • Method for sound source direction estimation based on time frequency masking and deep neural network

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[0059] Reference will now be made in detail to exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, the same numerals in different drawings refer to the same or similar elements unless otherwise indicated. The implementations described in the following exemplary examples do not represent all implementations consistent with the present invention. Rather, they are merely examples of apparatuses and methods consistent with aspects of the invention as recited in the appended claims.

[0060] figure 1 It is a flowchart of a sound source direction estimation method based on time-frequency masking and deep neural network according to an exemplary embodiment. The sound source orientation estimation method based on time-frequency masking and deep neural network can be used in electronic devices such as smart phones, smart homes, and computers. Such as figure 1 As shown, the sound s...

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Abstract

The invention discloses a method and device for sound source direction estimation based on time frequency masking and a deep neural network, electronic equipment and a storage medium, and belongs to the field of computer technologies. The method comprises the steps of acquiring a multichannel sound signal; carrying out framing, windowing and Fourier transform on each channel sound signal in the multichannel sound signal so as to form a short-time Fourier spectrum of the multichannel sound signal; carrying out an iterative operation on the short-time Fourier spectrum through a pre-trained neural network model, calculating ratio membranes corresponding to target signals in the multichannel sound signal, and fusing the multiple ratio membranes to form a single ratio membrane; and marking andweighting the multichannel sound signal according to the single ratio membrane to determine the orientation of the target sound source. The method and device for sound source direction estimation based on the time frequency masking and the deep neural network can have strong robustness in the environment with a low signal-to-noise ratio and strong reverberation, and improve the accuracy and stability of direction estimation for the target sound source.

Description

technical field [0001] The present disclosure relates to the field of computer application technology, and in particular to a sound source direction estimation method, device, electronic equipment, and storage medium based on time-frequency masking and deep neural networks. Background technique [0002] Sound source localization in noisy environments has many real-life applications, such as human-computer interaction, robotics, and beamforming. Traditionally, GCC-PHAT (Generalized Cross Correlation Phase Transform, generalized cross-correlation-phase transformation method), SRP-PHAT (Steered Response Power Phase Transform, phase transformation weighted controllable response power method) or MUSIC (Multiple Signal Classification, multiple Signal classification) and other sound source localization algorithms are the most common. However, these algorithms can only localize the loudest signal sources in the environment, which may not be the target speaker at all. For example, ...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G01S3/802
CPCG01S3/802
Inventor 不公告发明人
Owner ELEVOC TECH CO LTD
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