Audio labelling-processing method and device and computing device

Abstract

The invention provides an audio labelling-processing method and device. The method comprises the steps that original audio signals are obtained; the original audio signals are discretized to obtain target audios; characteristics of the target audios are extracted through a timing-sequence convolutional neural network (CNN) to obtain characteristic vectors of the target audios; clustering analysisis conducted on the characteristic vectors to obtain different categories of original audios corresponding to the characteristic vectors; according to the different categories of the original audios corresponding to the characteristic vectors, keywords in titles corresponding to the original audios in the same category are extracted, and one or more keywords are selected from the keywords according to a predetermined rule to serve as audio labels of the category. By adopting the scheme, efficient and accurate audio classification is achieved, high-accuracy and comprehensive audio labelling isachieve, and accordingly the search hit rate and recommending accuracy of audios can be improved.

Description

technical field [0001] The present invention relates to the technical field of audio processing, in particular to an audio tagging processing method, an audio tagging processing device, a computer storage medium, and a computing device. Background technique [0002] With the development and popularization of network technology, a large number of aggregated audio distribution platforms have emerged, which can provide network users with personalized audio services, including uploading, searching, recommending, playing, downloading and other services. In order to make it easier for users to search and use audio, and to make audio recommendations that meet users' interests and needs, it is necessary to accurately classify the massive audio on the platform and assign comprehensive and reasonable tags to each audio. Existing audio tagging methods usually use manual annotation, or simply extract keywords from the title and explanatory text of a single audio as tags, which have low ...

AI Technical Summary

Problems solved by technology

Existing audio tagging methods usually use manual annotation, or simply extract keywords from the title and explanatory text of a single audio as a tag, which has low operation efficiency, low accuracy, and small tag coverage.

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