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Sound source positioning method and system based on deep neural network

A deep neural network and sound source localization technology, applied in the field of sound source localization method and system based on deep neural network, can solve the problem of immature sound source localization method, etc., and achieve good scalability and good algorithm robustness. Effect

Active Publication Date: 2020-06-05
ZHEJIANG SCI-TECH UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the current research on sound source localization methods based on deep neural networks is still immature, and the existing results are more or less deficient.

Method used

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  • Sound source positioning method and system based on deep neural network
  • Sound source positioning method and system based on deep neural network
  • Sound source positioning method and system based on deep neural network

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Experimental program
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Embodiment 1

[0053] The first embodiment provides a sound source localization method based on a deep neural network, including a training phase of the deep neural network and a testing phase of the deep neural network, such as Figure 1-2 shown, including steps:

[0054] S11. Acquire the voice signal received by the microphone, and generate a voice data set from the acquired voice signal; wherein, the voice data set includes a training data set and a test data set;

[0055] S12. Perform first preprocessing on the speech signal in the generated speech data set;

[0056] S13. Calculate the phase-weighted generalized cross-correlation function of the sound source signal corresponding to the preprocessed speech signal;

[0057] S14. Obtain the time delay information corresponding to the peak of the phase-weighted generalized cross-correlation function, and use the obtained time delay information as the TDOA observation value of the sound source signal arriving at the microphone; and obtain th...

Embodiment 2

[0111] This embodiment provides a sound source localization system based on a deep neural network, including:

[0112] The first acquiring module is used to acquire the voice signal received by the microphone, and generate a voice data set from the acquired voice signal; wherein, the voice data set includes a training data set and a test data set;

[0113] A first preprocessing module, configured to perform first preprocessing on the speech signals in the generated speech data set;

[0114] A calculation module, configured to calculate a phase-weighted generalized cross-correlation function of the sound source signal corresponding to the preprocessed speech signal;

[0115] The second obtaining module is used to obtain the time delay information corresponding to the peak of the phase-weighted generalized cross-correlation function, and use the obtained time delay information as the TDOA observation value of the sound source signal arriving at the microphone; and obtain the tim...

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Abstract

The invention discloses a positioning method, which comprises the following steps: S1, acquiring a voice signal received by a microphone, and generating a voice data set; S2, preprocessing the voice signals in the voice data set; S3, calculating a phase weighted generalized cross-correlation function of the sound source signal corresponding to the voice signal; S4, acquiring time delay informationcorresponding to the peak of the phase weighted generalized cross-correlation function, and taking the time delay information as a TDOA observation value of the sound source signal reaching the microphone and obtaining an amplitude corresponding to the time delay information; S5, combining the TDOA observation value with the amplitude to serve as an input vector, taking a three-dimensional spaceposition coordinate corresponding to the sound source signal as an output vector, and combining the input vector and the output vector to generate a feature vector; S6, preprocessing the feature vector; S7, setting parameters related to the deep neural network, and training the deep neural network by using the feature vector of the training set to obtain a trained deep neural network; and S8, transmitting the input vector of the test set into the trained deep neural network for prediction to obtain a three-dimensional space coordinate of the sound source signal.

Description

technical field [0001] The invention relates to the technical field of indoor sound source localization, in particular to a sound source localization method and system based on a deep neural network. Background technique [0002] In recent years, smart service products (such as smart speakers, smart homes, etc.) have been widely used in real life. In order to obtain a good user experience, the human-computer interaction capabilities of products have attracted more and more attention. In human-computer interaction, voice communication is an indispensable part. People can directly issue voice passwords to order the machine to provide corresponding services, and the machine will recognize the voice passwords and provide corresponding services without manual operation. At present, in near-field speech recognition application scenarios (such as mobile phones), the quality of the speech signal received by the microphone is very high, and the speech recognition rate has met the act...

Claims

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Application Information

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IPC IPC(8): G01S5/22
CPCG01S5/22
Inventor 张巧灵唐柔冰马晗
Owner ZHEJIANG SCI-TECH UNIV