Environment Recognition for Digital Audio Forensics Using MPEG-7 and MEL Cepstral Features

Abstract

Environment recognition from digital audio for forensics application is a growing area of interest. However, compared to other branches of audio forensics, it is a less researched one. Especially less attention has been given to detect environment from files where foreground speech is present, which is a forensics scenario. In this paper, we perform several experiments focusing on the problems of environment recognition from audio particularly for forensics application. Experimental results show that the task is easier when audio files contain only environmental sound than when they contain both foreground speech and background environment. We propose a full set of MPEG-7 audio features combined with mel frequency cepstral coefficients (MFCCs) to improve the accuracy. In the experiments, the proposed approach significantly increases the recognition accuracy of environment sound even in the presence of high amount of foreground human speech.

Evaluation of speaker de-identification based on voice gender and age conversion

“…MFCC coefficients together with prosodic parameters are often used in speaker recognition systems [18] which can also be used to check the de-identification performance. However, because of our previous good experience, different types of speech features comprising basic and supplementary spectral properties complemented with supra-segmental parameters were used in this experiment for GMM creation, training, and classification.…”

Audio–Visual Emotion-Aware Cloud Gaming Framework

“…This section investigates the feasibility of MPEG-7 low level audio descriptors (features) in the field of emotion recognition. The main reason of using these descriptors is that they were found to be more efficient than the traditional speech features such as Mel frequency cepstral coefficients (MFCC) and linear predictive cepstral coefficients (LPCC) in many applications such as speaker recognition, environment recognition [32], and musical instrument classification. a) MPEG-7 low level audio descriptor: MPEG-7 features are originally developed for multimedia indexing, which contains both video and audio parts [33].…”

Blind identification of source mobile devices using VoIP calls

“…These approaches include: (a) environment-based techniques in which the the frequency spectra are forced through the recording environment, (b) device-based techniques in which the frequency spectra are produced by a recording device, and (c) ENF-based techniques in which the frequency spectra are generated by the power source of the recording device [3]. Although advanced research has been conducted on ENF-based techniques [4], [5] and environmentbased techniques [6], [7], few have explored the application of device-based techniques in real-time forensics [1], [8]. Device-based techniques are based on blind source camera identification in image forensics [9], [10], [11].…”