The DIarization of SPeaker and LAnguage in Conversational Environments
(DISPLACE) 2024 challenge is the second in the series of DISPLACE challenges,
which involves tasks of speaker diarization (SD) and language diarization (LD)
on a challenging multilingual conversational speech dataset. In the DISPLACE
2024 challenge, we also introduced the task of automatic speech recognition
(ASR) on this dataset. The dataset containing 158 hours of speech, consisting
of both supervised and unsupervised mono-channel far-field recordings, was
released for LD and SD tracks. Further, 12 hours of close-field mono-channel
recordings were provided for the ASR track conducted on 5 Indian languages. The
details of the dataset, baseline systems and the leader board results are
highlighted in this paper. We have also compared our baseline models and the
team's performances on evaluation data of DISPLACE-2023 to emphasize the
advancements made in this second version of the challenge.

DIarization of SPeaker and LAnguage in Conversational Environments (DISPLACE) 2024 challenge involves tasks of speaker diarization (SD), language diarization (LD), and automatic speech recognition (ASR) on a multilingual conversational speech dataset, with details of the dataset, baseline systems, and performance comparison with DISPLACE-2023.