Fearless steps: Advancing speech and language processing for naturalistic audio streams from Earth to the Moon with Apollo

Abstract

NASA’s Apollo program represents one of the greatest achievements of mankind in the 20th century. CRSS-UTDallas has completed an effort to digitize and establish an Apollo audio corpus. The entire Apollo mission speech data consists of well over ~100,000 hours. The focus of this effort is to contribute to the development of Spoken Language Technology based algorithms to analyze and understand various aspects of conversational speech. Towards achieving this goal, a new 30 track analog audio decoder was designed using NASA Soundscriber. We have digitized 19,000 hours of data from Apollo 11,13,1 missions: named “Fearless Steps”. An automated diarization and transcript generation solution was developed based on deep neural networks (DNN) automatic speech recognition (ASR) along with Apollo mission specific language models. Demonstration of speech technologies including speech activity detection (SAD), speaker identification (SID), and ASR are shown for segments of the corpus. We will release this corpus to the SLT community. The data provide an opportunity for challenging tasks in various SLT areas. We have also defined and proposed 5 tasks as a part of a community based SLT challenge. The five challenges are as follows: (1) automatic speech recognition, (2) speaker identification, (3) speech activity detection, (4) speaker diarization, and (5) keyword spotting and joint topic/sentiment detection. All data, transcripts, and guidelines for employing the fearless steps corpus will be made freely available to the community.