Music style identification method and device, storage medium and electronic equipment
A recognition method and music technology, applied in neural learning methods, speech analysis, electroacoustic musical instruments, etc., can solve problems such as difficulties, and achieve the effect of improving accuracy, improving classification efficiency, and efficient recognition
Pending Publication Date: 2022-03-04
HANGZHOU NETEASE CLOUD MUSIC TECH CO LTD
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Problems solved by technology
In the current music style research, there are difficulties in how to accurately define a specific type of music style and efficiently and automatically identify this type of music style
Method used
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[0064] The principle and spirit of the present disclosure will be described below with reference to several exemplary embodiments. It should be understood that these embodiments are given only to enable those skilled in the art to better understand and implement the present disclosure, rather than to limit the scope of the present disclosure in any way. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.
[0065] Those skilled in the art know that the embodiments of the present disclosure may be implemented as a system, device, device, method or computer program product. Therefore, the present disclosure can be embodied in the form of complete hardware, complete software (including firmware, resident software, microcode, etc.), or a combination of hardware and software.
[0066] According to the embodiments of the present disclosure, a music style recogniti...
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The embodiment of the invention relates to the technical field of audio processing, in particular to a music style recognition method and device, a storage medium and electronic equipment. The music style recognition method comprises the steps of performing segmentation processing on a to-be-recognized audio to obtain a plurality of audio clips; extracting audio features of each audio clip, inputting the audio features into a trained music style recognition model based on a convolutional neural network, and recognizing whether each audio clip belongs to a target music style; wherein the music style identification model comprises a plurality of groups of convolutions with a plurality of convolution layer numbers; obtaining a target music style confidence coefficient of the to-be-identified audio according to the proportion of the audio clip which is identified to belong to the target music style in the plurality of audio clips; and obtaining a music style recognition result of the to-be-recognized audio according to the target music style confidence coefficient and a target corresponding relationship between the confidence coefficient interval and the music style classification result. According to the invention, automatic identification based on the target music style can be accurately and efficiently carried out on the audio file.
Description
technical field [0001] Embodiments of the present disclosure relate to the technical field of audio processing, and more specifically, embodiments of the present disclosure relate to a music style recognition method, device, storage medium, and electronic device. Background technique [0002] This section is intended to provide background or context for implementations of the disclosure that are recited in the claims and the description herein is not admitted to be prior art by inclusion in this section. [0003] To manually identify the music style, it is necessary to listen to the whole song to determine the specific category. In the current music style research, there are difficulties in how to accurately define a specific type of music style and efficiently and automatically identify this type of music style. Contents of the invention [0004] In the current music style research, only a broad classification of music styles has been carried out. With the development o...
Claims
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Login to View More IPC IPC(8): G10L25/51G10L25/30G06N3/04G06N3/08
CPCG10L25/51G10L25/30G06N3/08G10H2210/031G10H2210/036G10H2250/311G06N3/045
Inventor 邓阳李承鑫曹偲刘华平赵翔宇黄安麒
Owner HANGZHOU NETEASE CLOUD MUSIC TECH CO LTD