Digital multimedia content analysis aims to verify authenticity and identify manipulation.
- Photographs and Video recordings - analysis of metadata (EXIF, GPS), frame rate and digital signatures
- Audio recordings
- Audio enhancement - Audio enhancement is method, which includes a set of techniques for removing unwanted noise, improving speech intelligibility and reconstructing damaged recordings. Techniques include noise filtering, echo removal, and frequency spectrum balancing. Advanced algorithms can eliminate background sounds such as traffic noise or other people’s voices. Key tools for audio enhancement include iZotope RX, Adobe Audition, and Audacity.
- Speaker identification - Speaker identification is a method used to confirm a person’s identity based on their voice. The analysis is based on unique characteristics of speech such as pitch, tempo, intonation and articulation. It involves evaluating and comparing questioned audio recordings with reference samples using auditory-perceptual and acoustic-instrumental techniques. Major challenges include recording quality, background noise, emotional variations and voice masking.
- Audio authenticity analysis - Audio authenticity analysis verifies whether a disputed audio recording was manipulated. This method involves a series of tests that detect possible signs of editing, insertion, deletion and other forms of audio processing. Techniques include spectral analysis, frequency and timeline discrepancy detection, and metadata analysis. The emergence of deepfake technology presents a major challenge because of its use in advanced audio forgery.
