CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings

• URL: http://arxiv.org/abs/2004.09249v2
• Date: Sat, 2 May 2020 11:04:49 GMT
• Title: CHiME-6 Challenge:Tackling Multispeaker Speech Recognition for Unsegmented Recordings
• Authors: Shinji Watanabe, Michael Mandel, Jon Barker, Emmanuel Vincent, Ashish Arora, Xuankai Chang, Sanjeev Khudanpur, Vimal Manohar, Daniel Povey, Desh Raj, David Snyder, Aswin Shanmugam Subramanian, Jan Trmal, Bar Ben Yair, Christoph Boeddeker, Zhaoheng Ni, Yusuke Fujita, Shota Horiguchi, Naoyuki Kanda, Takuya Yoshioka, Neville Ryant
• Abstract summary: We organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6) The challenge revisits the previous CHiME-5 challenge and further considers the problem of distant multi-microphone conversational speech diarization and recognition. This paper provides a baseline description of the CHiME-6 challenge for both segmented multispeaker speech recognition and unsegmented multispeaker speech recognition.
• Score: 87.37967358673252
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Following the success of the 1st, 2nd, 3rd, 4th and 5th CHiME challenges we organize the 6th CHiME Speech Separation and Recognition Challenge (CHiME-6). The new challenge revisits the previous CHiME-5 challenge and further considers the problem of distant multi-microphone conversational speech diarization and recognition in everyday home environments. Speech material is the same as the previous CHiME-5 recordings except for accurate array synchronization. The material was elicited using a dinner party scenario with efforts taken to capture data that is representative of natural conversational speech. This paper provides a baseline description of the CHiME-6 challenge for both segmented multispeaker speech recognition (Track 1) and unsegmented multispeaker speech recognition (Track 2). Of note, Track 2 is the first challenge activity in the community to tackle an unsegmented multispeaker speech recognition scenario with a complete set of reproducible open source baselines providing speech enhancement, speaker diarization, and speech recognition modules.

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