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Voice wake-up method and system based on binary residual neural network

A voice wake-up and neural network technology, applied in neural learning methods, biological neural network models, speech analysis, etc., can solve the problems of large amount of calculation, large memory usage, high complexity of deep convolutional neural network models, etc., to improve recognition The effect of reducing the rate, reducing the amount of parameters and the amount of calculation

Active Publication Date: 2022-07-05
中科南京智能技术研究院
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Problems solved by technology

However, high-performance deep convolutional neural network models are highly complex, computationally intensive, and often require a large amount of memory, so it is difficult to deploy them to mobile terminals with small memory

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  • Voice wake-up method and system based on binary residual neural network

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Embodiment Construction

[0032] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, but not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0033] The purpose of the present invention is to provide a voice wake-up method and system based on a binary residual neural network, which can improve the recognition accuracy of voice wake-up while reducing the amount of data storage and calculation.

[0034] In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below wi...

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Abstract

The invention discloses a voice wake-up method and system based on a binary residual neural network, and relates to the technical field of voice wake-up. The method comprises the following steps: acquiring a to-be-recognized audio file to obtain a to-be-processed voice signal; performing feature extraction on the to-be-processed voice signal to obtain a Mel spectrum feature frame; constructing a binary residual neural network model; inputting the Mel spectrum feature frame into a trained binary residual neural network model to obtain a keyword probability value and a non-keyword probability value; and judging whether to perform voice wake-up according to the probability value. According to the invention, the recognition accuracy of voice wake-up can be improved while the data storage amount and the calculation amount are reduced.

Description

technical field [0001] The invention relates to the technical field of voice wake-up, in particular to a voice wake-up method and system based on a binary residual neural network. Background technique [0002] The voice wake-up system usually runs on mobile devices, which have small memory and limited computing power. Therefore, the voice wake-up system should simultaneously meet the requirements of high accuracy, small memory used for operation, and less calculation. However, high-performance deep convolutional neural network models are complex and computationally intensive, and often require a lot of memory, so it is difficult to deploy them to mobile devices with small memory. SUMMARY OF THE INVENTION [0003] The purpose of the present invention is to provide a voice wake-up method and system based on a binary residual neural network, which can improve the recognition accuracy of voice wake-up while reducing the amount of data storage and calculation. [0004] For ach...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G10L15/02G10L15/06G10L15/16G10L15/22G06N3/04G06N3/08
CPCG10L15/02G10L15/063G10L15/16G10L15/22G06N3/08G10L2015/223G06N3/045Y02D30/70
Inventor 王啸尚德龙周玉梅
Owner 中科南京智能技术研究院
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