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Robust audio hash function defines a feature vector that characterises the audio signal, independent of content preserving manipulations, such as MP3 compression, amplitude boosting/cutting, low-pass filtering etc. In this study, the authors propose a new audio hash function based on the non-negative matrix factorisation (NMF) of mel-frequency cepstral coefficients (MFCCs). Their work is motivated...
Robust audio hashing defines a feature vector that characterises the audio signal, independent of content preserving manipulations, such as MP3 compression, amplitude boosting/cutting, hiss reduction, and so on. It provides a tool for fast and reliable identification of content in audio communications. In this study, the authors propose a new audio hashing based on discrete wavelet transform and non-negative...
Learning is a central task in computer science, and there are various formalisms for capturing the notion. One important model studied in computational learning theory is the PAC model of Valiant (CACM 1984). On the other hand, in cryptography the notion of "learning nothing'' is often modelled by the simulation paradigm: in an interactive protocol, a party learns nothing if it can produce a...
We consider the question of whether P ne NP implies that there exists some concept class that is efficientlyrepresentable but is still hard to learn in the PAC model of Valiant (CACM '84), where the learner is allowed to output any efficient hypothesis approximating the concept, including an "improper" hypothesis that is not itself in the concept class. We show that unless the polynomial...
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