The Second DISPLACE Challenge : DIarization of SPeaker and LAnguage in Conversational Environments
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.
Code (0)
등록된 구현이 없습니다.
Tasks
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)speaker-diarizationSpeaker Diarizationspeech-recognitionSpeech RecognitionSimilar Papers 제목 키워드 기반
TCG CREST System Description for the Second DISPLACE Challenge
In this report, we describe the speaker diarization (SD) and language diarization (LD) systems developed by our team for the Second DISPLACE Challenge, 2024. Our contributions were dedicated to Track 1 for SD and Track 2…
Action DetectionActivity Detectionspeaker-diarizationSpeaker Diarization+1TalTech-IRIT-LIS Speaker and Language Diarization Systems for DISPLACE 2024
This paper describes the submissions of team TalTech-IRIT-LIS to the DISPLACE 2024 challenge. Our team participated in the speaker diarization and language diarization tracks of the challenge. In the speaker diarization …
speaker-diarizationSpeaker DiarizationSpeech SeparationDISPLACE Challenge: DIarization of SPeaker and LAnguage in Conversational Environments
In multilingual societies, social conversations often involve code-mixed speech. The current speech technology may not be well equipped to extract information from multi-lingual multi-speaker conversations. The DISPLACE …
speaker-diarizationSpeaker DiarizationSystem Description for the Displace Speaker Diarization Challenge 2023
This paper describes our solution for the Diarization of Speaker and Language in Conversational Environments Challenge (Displace 2023). We used a combination of VAD for finding segfments with speech, Resnet architecture …
Clusteringspeaker-diarizationSpeaker DiarizationSummary of the DISPLACE Challenge 2023 -- DIarization of SPeaker and LAnguage in Conversational Environments
In multi-lingual societies, where multiple languages are spoken in a small geographic vicinity, informal conversations often involve mix of languages. Existing speech technologies may be inefficient in extracting informa…
speaker-diarizationSpeaker Diarization