Audio Manipulation Detection
Hi everyone!
I am looking for a software, platform, or automated solution to analyze a large batch of exported WhatsApp voice messages (.opus files) to determine how they were recorded.
Specifically, I want to categorize them into three types:
- Natural: Recorded in one continuous go.
- Studio-quality: Professionally produced/edited.
- Highly edited: The user frequently used the WhatsApp pause/break button to piece the message together perfectly.
The Challenge: I ran some files through basic AI tools like Cleanvoice, but they often misinterpret the edits as normal breathing or simple pauses. However, when I look at the Audacity Spectrogram, I can clearly see hard cuts, phase shifts, and abrupt changes in the room tone (noise floor) right where the pause button was pressed.
Since I have hundreds of files, checking the spectrogram manually for each one is not feasible.
Is there any audio-forensics tool, python library (like librosa), or platform that can batch-analyze noise floor continuity or phase breaks to automatically flag these cuts?
Thanks in advance!