Automatic Speech Codec Identification with Applications to Tampering Detection of Speech Recordings

Abstract

In this work many versions of CELP codecs are explored, and an observation is made that different codebooks are used to encode noisy part of residual. Taking advantage of noise patterns they generated, an algorithm was proposed to detect GSM-AMR,EFR,HR and SILK codecs. Another partly knowledge-based and partly data driven algorithm is also proposed to improve the performance for SILK. Then it's extended to identify subframe offset to do tampering detection of cellphone speech recordings.