Abstract
The focus of audio retrieval research is to find the target audio faster and more accurately in the audio database according to a query audio. In this paper, a low-dimensional audio fingerprint extraction method based on local linear embedding (LLE) and an efficient hierarchical retrieval method are proposed. In the fingerprint extraction part, the audio fingerprint is computed by the energy comparison. The proposed method reduces the dimensionality of the energy vector and the number of energy comparisons by introducing the LLE algorithm, which results in a low-dimensional audio fingerprint. The retrieval part is divided into two stages, which are hash value retrieval for single-frame audio fingerprints and fingerprint block retrieval for consecutive multi-frame audio fingerprints. In the first stage, the reference audios with the same hash value as the query audio are filtered out as candidates. In the second stage, the exact retrieval result is found by calculating the similarity between the query fingerprint block and the reference fingerprint block. The proposed method reduces the computational complexity of fingerprint matching by narrowing the scope of retrieval, thus improving the retrieval speed. In the experimental part, the effectiveness of the proposed method is evaluated and compared with some state-of-the-art methods. The experiments prove that the retrieval accuracy and computation speed can reach a high level after using the proposed method.
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Acknowledgments
This work has been supported by the National Natural Science Foundation of China (No. 61971015) and the Cooperative Research Project of BJUT-NTUT (No. NTUT-BJUT-110–05).
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Li, T., Jia, M., Cao, X. (2021). A Hierarchical Retrieval Method Based on Hash Table for Audio Fingerprinting. In: Huang, DS., Jo, KH., Li, J., Gribova, V., Bevilacqua, V. (eds) Intelligent Computing Theories and Application. ICIC 2021. Lecture Notes in Computer Science(), vol 12836. Springer, Cham. https://doi.org/10.1007/978-3-030-84522-3_13
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