DISPLACE Corpus

The DISPLACE challenge entailed a first of kind task to perform speaker and language diarization on the same data, <br> as the data contains multi-speaker social conversations in multi-lingual code-mixed speech. In multi-lingual communities, <br> social conversations frequently involve code-mixed and code-switched speech. In such cases, various speech processing <br> systems need to perform the speaker and language segmentation before any downstream task. The current speaker diarization <br> systems are not equipped to handle multi-lingual conversations, while the language recognition systems may not be able to <br> handle the same talker speaking in multiple languages within the same recording. With this motivation, the DISPLACE challenge <br> addressed Speaker Diarization (SD) in multi-lingual settings and Language Diarization (LD) in multi-speaker settings, using <br> the same underlying dataset. For this challenge, a natural multi-lingual, multi-speaker conversational dataset was distributed. More details about the dataset can be found at https://www.isca-speech.org/archive/pdfs/interspeech_2023/baghel23_interspeech.pdf <br>