Melody Feature Clustering and Optimization for Query-by-humming
Query-by-humming is an important branch of audio retrieval, and it can provide users with a new and convenient experience.During the retrieval process, since there are unignorable differences between different humming of the same song, it is difficult to obtain ideal results by accurate matching of...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | Chinese |
| Published: |
Harbin University of Science and Technology Publications
2022-02-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=2057 |
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| Summary: | Query-by-humming is an important branch of audio retrieval, and it can provide users with a new and convenient experience.During the retrieval process, since there are unignorable differences between different humming of the same song, it is difficult to obtain ideal results by accurate matching of the melody features.To solve this problem, the optimized initial clustering center k-means (OICC k-means) is introduced in the query-by-humming system. By clustering melody features to fully learn the structural similarity between different melody features, the melody features with similar structures are divided into the same cluster and the clusters are numbered, so as to provide more effective matching of melody features at the back end label. Meanwhile, considering that the clustered melody features can be further characterized, the clustered tags are used as the input tags of deep belief networks (DBN) and feature extraction is performed to obtain stronger discriminative characteristics the high-level melody features of the melody, thereby effectively improving the robustness of melody features.After obtaining the high-level melody features, it is necessary to use the cluster category as a matching tag and perform a humming search. Experimental results show that the proposed method can effectively improve the performance of humming retrieval system. |
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| ISSN: | 1007-2683 |