The NASA Apollo program relied on a massive team of dedicated scientists, engineers, and specialists working seamlessly together in a cohesive manner to accomplish probably one of mankind’s greatest technological achievements in history. The Fearless Steps Initiative by UTD-CRSS has led to the digitization of 19,000 hours of analog audio data and development of algorithms to extract meaningful information from this multichannel naturalistic data. Further exploring the intricate communication characteristics of problem solving on the scale as complex as going to the moon can lead to the development of novel algorithms beneficial for speech processing and conversational understanding in challenging environments. As an initial step to motivate a streamlined and collaborative effort from the speech and language community, we propose The FEARLESS STEPS (FS-1) Challenge.

Most of the data for the Apollo Missions is unlabeled and has thus far motivated the development of some unsupervised and semi-supervised speech algorithms. The Challenge Tasks for this session encourage the development of such solutions for core speech and language tasks on data with limited ground-truth/low resource availability, and serves as the first step towards extracting high level information from such massive unlabeled corpora.

This edition of the Fearless Steps Challenge with include all or most of the following tasks:

1. Speech Activity Detection: SAD
2. Speaker Diarization: SD
3. Speaker Identification: SID
4. Automatic Speech Recognition: ASR
5. Sentiment Detection: SENTIMENT

The necessary ground truth labels and transcripts will be provided for the training/development set data.

For more information, Please visit the release website: https://exploreapollo.org/

The Corpus Data can be found at http://fearlesssteps.exploreapollo.org/

Organizers:

• John H.L. Hansen (Center for Robust Speech Systems, Univ. of Texas at Dallas, USA)
• Abhijeet Sangwan (Speetra Inc., Electrical & Computer Engineering Department at Univ. of Texas at Dallas, USA)
• Lakshmish Kaushik (Staff Researcher, SONY, Foster City, California, USA)
• Chengzhu Yu (Researcher, Tencent AI Lab, Seattle, USA)
• Aditya Joglekar (Univ. of Texas at Dallas, USA)
• Meena M.C. Shekar (Center for Robust Speech Systems, Univ. of Texas at Dallas, USA)