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Audio high-level semantic feature extraction method and system for overlapped sound event detection

A high-level semantic and event detection technology, applied in voice analysis, instruments, etc., can solve the problems of large amount of calculation, time-consuming and labor-intensive, etc., and achieve the effect of improving accuracy

Inactive Publication Date: 2020-03-27
FUZHOU UNIV
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  • Claims
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AI Technical Summary

Problems solved by technology

[0007] However, when the traditional physical feature extraction technology is applied to the detection of overlapping sound events, most of them need to start from the sound signal itself, dig out its time-frequency characteristics, make assumptions, and establish a physical model. Many parameters need to be fine-tuned manually, which is time-consuming and laborious. , a large amount of calculation

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  • Audio high-level semantic feature extraction method and system for overlapped sound event detection

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Embodiment Construction

[0027] The present invention will be further described below in conjunction with the accompanying drawings and embodiments.

[0028] It should be pointed out that the following detailed description is exemplary and is intended to provide further explanation to the present application. Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this application belongs.

[0029] It should be noted that the terminology used here is only for describing specific implementations, and is not intended to limit the exemplary implementations according to the present application. As used herein, unless the context clearly dictates otherwise, the singular is intended to include the plural, and it should also be understood that when the terms "comprising" and / or "comprising" are used in this specification, they mean There are features, steps, operations, means, components and / or combina...

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Abstract

The invention relates to an audio high-level semantic feature extraction method and system for overlapped sound event detection, and the method comprises the steps: firstly constructing an audio filetraining data set, and selecting Mel energy features for audio files of different scenes in the training set to form an input matrix; secondly, constructing a CBG deep convolutional neural network, and inputting the input matrix obtained in the step S1 into the CBG deep convolutional neural network for training; and finally, for a given audio file, extracting Mel energy features of the given audiofile, and inputting the Mel energy features into the trained CBG deep convolutional neural network to obtain high-level semantic feature output. According to the method, traditional audio physical features are converted into high-level semantic features, so that the precision of subsequent detection can be improved.

Description

technical field [0001] The invention relates to the technical field of overlapping sound event processing of complex audio, in particular to an audio high-level semantic feature extraction method and system for overlapping sound event detection. Background technique [0002] Audio is divided into simple audio and complex audio. Simple audio refers to those that contain only one type of audio event, such as pure speech, footsteps, etc. Complex audio refers to audio that contains multiple audio events, such as a slightly longer period of audio in a movie, which may contain gunshots, speech, music, etc., and these audio events may overlap in time. [0003] Most of the sound features used in sound event detection follow the characteristics of speech signals in the time-frequency domain, cepstrum domain and frequency domain, and also perform multiple feature fusion based on the features of time-frequency domain, cepstrum domain and frequency domain. Summarizing the methods of D...

Claims

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Application Information

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IPC IPC(8): G10L25/30G10L25/03
CPCG10L25/30G10L25/03
Inventor 余春艳刘煌李明达
Owner FUZHOU UNIV
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