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Source Tracing of Audio Deepfake Systems: MLAAD Source Tracing Protocol

<p>This data was created as part of the work entitled "Source Tracing of Audio Deepfake Systems", published in Interspeech 2024.</p> <p>In doing our training, development, and testing, Pindrop used WAV files from the Multi-Language Audio Anti-Spoof Dataset (MLAAD) and the M-AILABS Speech Dataset. You can obtain copies of these same WAV files directly from the developers here:<br>MLAAD (version 1): <a href="https://owncloud.fraunhofer.de/index.php/s/tL2Y1FKrWiX4ZtP#editor" target="_blank" rel="noopener">https://owncloud.fraunhofer.de/index.php/s/tL2Y1FKrWiX4ZtP#editor</a><br>M-AILABS: <a href="https://www.caito.de/2019/01/03/the-m-ailabs-speech-dataset/" target="_blank" rel="noopener">https://www.caito.de/2019/01/03/the-m-ailabs-speech-dataset/</a></p>

ShareScore

20/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
8
Reuse readiness
0
Engagement
4