Audio Signal Processing Using Time-Frequency Approaches: Coding, Classification, Fingerprinting, and Watermarking
نویسندگان
چکیده
منابع مشابه
Audio Signal Processing Using Time-Frequency Approaches: Coding, Classification, Fingerprinting, and Watermarking
Audio signals are information rich nonstationary signals that play an important role in our day-to-day communication, perception of environment, and entertainment. Due to its non-stationary nature, timeor frequency-only approaches are inadequate in analyzing these signals. A joint time-frequency (TF) approach would be a better choice to efficiently process these signals. In this digital era, co...
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A novel non-blind digital audio watermarking scheme using time-frequency based operations is presented. The digital audio samples are first segmented into frames and the frames are transformed into the frequency domain. Frequency components are then added or removed. The amplitude of the components added or removed are determined under the guidance of Psychoacoustic Model I. Inverse transform i...
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Although not a new issue, music piracy has acquired a new status in the digital era, as recordings can be easily copied and distributed. Watermarking has been proposed as a solution to this problem. It consists in embedding into the audio signal an inaudible mark containing copyright information. A different approach, called fingerprinting, consists in extracting a “fingerprint” from the audio ...
متن کاملDigital Audio Watermarking using Frequency Masking Technique
There is a need of an effective watermarking technique for copyright protection and authentication of intellectual Property [12]. In this work we propose a digital watermarking technique which makes use of simultaneous frequency masking to hide the watermark information into host. The algorithm is based on Psychoacoustic Auditory Model and Spread Spectrum theory [2]. It generates a watermark si...
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We propose a new audio fingerprinting method that adapts findings from the field of blind astrometry to define simple, efficiently representable characteristic feature combinations called quads. Based on these, an audio identification algorithm is described that is robust to large amounts of noise and speed, tempo and pitch-shifting distortions. In addition to reliably identifying audio queries...
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ژورنال
عنوان ژورنال: EURASIP Journal on Advances in Signal Processing
سال: 2010
ISSN: 1687-6180
DOI: 10.1155/2010/451695