Abstract
The performance of a perceptual hashing system, which is often measured by discrimination and robustness, is directly related to the features that the system extracts. In this letter, a new speech hashing scheme based on short-time stability is presented. The characteristic of natural speech that the principal components of linear prediction coefficients among neighboring frames tend to be very similar is utilized to generate the hash sequence. Experimental results demonstrate the effectiveness of the proposed scheme in terms of discrimination and robustness.
This work was supported in part by the National Natural Science Foundation of China (No. 60872115), in part by the Shanghai’s Key Discipline Development Program (No.J50104), and in part by the International Cooperation Foundation Program of Shanghai (No. 075107035).
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Chen, N., Wan, WG. (2009). Speech Hashing Algorithm Based on Short-Time Stability. In: Alippi, C., Polycarpou, M., Panayiotou, C., Ellinas, G. (eds) Artificial Neural Networks – ICANN 2009. ICANN 2009. Lecture Notes in Computer Science, vol 5769. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04277-5_43
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DOI: https://doi.org/10.1007/978-3-642-04277-5_43
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