InMAF: Indexing Music Databases via Multiple Acoustic Features

Summary: InMAF proposes compact descriptors for scalable indexing of music databases using multiple acoustic features. It blends perception-driven features with PCA and neural nets to boost retrieval accuracy and distortion robustness over spectral baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 3884
Venue: SIGMOD
Year: 2006
Pagerank: -
Overall Rank: 13,824 | 5.16%
DOI: 10.1145/1142473.1142587

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Authors

1. Jialie Shen (University of New South Wales)
2. John Shepherd (University of New South Wales)
3. Anne H.H. Ngu (Texas State University)

BibTeX Citation

@inproceedings{shen_sigmod06,
        title = {{InMAF: Indexing Music Databases via Multiple Acoustic Features}},
        author = {Shen, Jialie and Shepherd, John and Ngu, Anne H.H.},
        series = {{SIGMOD} '06},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1142473.1142587},
        url = {https://dl.acm.org/doi/10.1145/1142473.1142587},
        year = {2006}
}

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