An overview of audio information retrieval
Multimedia Systems - Special issue on audio and multimedia
Introduction to data compression (2nd ed.)
Introduction to data compression (2nd ed.)
A general audio classifier based on human perception motivated model
Multimedia Tools and Applications
Generalized Lempel–Ziv Compression for Audio
IEEE Transactions on Audio, Speech, and Language Processing
A Survey of Audio-Based Music Classification and Annotation
IEEE Transactions on Multimedia
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In this paper, we undertake an initial study evaluation of a recently developed audio compression approach; Audio Compression Exploiting Repetition (ACER). This is a novel compression method that employs dictionary-based techniques to encode repetitive musical sequences that naturally occur within musical audio. As such, it is a lossy compression technique that exploits human perception to achieve data reduction. To evaluate the output from the ACER approach, we conduct a pilot evaluation of the ACER coded audio, by employing both objective and subjective testing, to validate the ACER approach. Results show that the ACER approach is capable of producing compressed audio that varies in subjective and objective and quality grades that are inline with the amount of compression desired; configured by setting a similarity threshold value. Several lessons are learned and suggestion given as to how a larger, enhanced series of listening tests will be taken forward in future, as a direct result of the work presented in this paper.