Declipping of Audio Signals Using Perceptual Compressed Sensing
| Autor: | Toon van Waterschoot, Moritz Diehl, Bruno Defraene, Marc Moonen, Naim Mansour, Steven De Hertogh |
|---|---|
| Rok vydání: | 2013 |
| Předmět: |
Auditory perception
Audio signal Acoustics and Ultrasonics Computer science business.industry media_common.quotation_subject Speech recognition Speech processing Compressed sensing Signal recovery Perception Computer vision Minification Artificial intelligence Electrical and Electronic Engineering Sound quality business media_common |
| Zdroj: | IEEE Transactions on Audio, Speech, and Language Processing. 21:2627-2637 |
| ISSN: | 1558-7924 1558-7916 |
| Popis: | The restoration of clipped audio signals, commonly known as declipping, is important to achieve an improved level of audio quality in many audio applications. In this paper, a novel declipping algorithm is presented, jointly based on the theory of compressed sensing (CS) and on well-established properties of human auditory perception. Declipping is formulated as a sparse signal recovery problem using the CS framework. By additionally exploiting knowledge of human auditory perception, a novel perceptual compressed sensing (PCS) framework is devised. A PCS-based declipping algorithm is proposed which uses $\ell _{1}$ -norm type reconstruction. Comparative objective and subjective evaluation experiments reveal a significant audio quality increase for the proposed PCS-based declipping algorithm compared to CS-based declipping algorithms. |
| Databáze: | OpenAIRE |
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