3 accepted papers
Acquisition device clustering from speech recordings is a new and critical problem in the field of speech forensic, which aims at merging speech recordings acquired by the same device into one cluster without both pre-knowing prior information of the processed data and pre-training classifier. We pr…
This paper describes a method to extract time-frequency (TF) audio features by tensor-based sparse approximation for sound effects classification. In the proposed method, the observed data is encoded as a higher-order tensor and discriminative features are extracted in spectrotemporal domain. Firstl…
Source recording device recognition is an important emerging research field of digital media forensic. Most of the prior literature focus on the recording device identification problem. In this study we propose a source cell phone verification scheme based on sparse representation. We employed Gauss…