Sound event labeling and identification method adopting double Token tags

A recognition method and event technology, applied in the field of acoustic event detection, can solve the problems of poor recognition accuracy, low labeling accuracy, and reduced labor cost of audio data sets.
CN113140226AActive Publication Date: 2021-07-20GUILIN UNIV OF ELECTRONIC TECH
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Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
GUILIN UNIV OF ELECTRONIC TECH
Publication Date
2021-07-20

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Abstract

The invention discloses a sound event labeling and recognition method adopting double Token tags, which is characterized by comprising a sound event labeling process and a sound event recognition process, and the sound event labeling process is as follows: 1-1) realizing an audio tag form; 1-2) completing all audio annotations in the data set; the identification process comprises the following steps: 2-1) constructing an audio data set; 2-2) extracting audio data preprocessing and feature; 2-3) amplifying the audio data; 2-4) building a convolutional recurrent neural network; 2-5) training the convolutional recurrent neural network learning detection model, and 2-6) using the trained detection model to identify the audio to be detected. According to the method, the accuracy rate can be guaranteed, meanwhile, the sound event recognition range is widened at a low cost, accurate sound event detection and monitoring in the living environment of people can be achieved, and therefore the method better serves for smart city construction.
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Description

Technical field

[0001] The present invention relates to the field of acoustic event detection, and is specifically a sound event label and identification method using a dual Token tag. Background technique

[0002] In people's living environment, all kinds of sounds carry a large number of physical event information about the daily environment and among them. Sound Events Detection (SED) studies can help people know their sound scenes, identify various sound source categories, and have important practical significance. Can be applied to urban environment noise monitoring, public space safety monitoring, indoor environment, children's behavioral monitoring, such as smart cities and wisdom home scenes, such as acoustic monitoring application scenarios, can automatically detect gunshots, scream, object burning In human-machine interaction, hearing sensation, meets the various types of inspection needs in society.

[0003] Acoustic event detection tasks depend on the signal processin...

Claims

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