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1. UNDERSTANDING SPEAKER ROLES ON A NATURALISTIC CORPUS: FEARLESS STEPS APOLLO 11

   Chandra-Shekar, M.M. ; Hansen, J.H.L. ( February 2023 , NASA Human Research Program Investigators Conference)

   INTRODUCTION: Apollo-11 (A-11) was the first manned space mission to successfully bring astronauts to the moon and return them safely. Effective team based communications is required for mission specialists to work collaboratively to learn, engage, and solve complex problems. As part of NASA’s goal in assessing team and mission success, all vital speech communications between these personnel were recorded using the multi-track SoundScriber system onto analog tapes, preserving their contribution in the success of one of the greatest achievements in human history. More than +400 personnel served as mission specialists/support who communicated across 30 audio loops, resulting in +9k hours of data for A-11. To ensure success of this mission, it was necessary for teams to communicate, learn, and address problems in a timely manner. Previous research has found that compatibility of individual personalities within teams is important for effective team collaboration of those individuals. Hence, it is essential to identify each speaker’s role during an Apollo mission and analyze group communications for knowledge exchange and problem solving to achieve a common goal. Assessing and analyzing speaker roles during the mission can allow for exploring engagement analysis for multi-party speaker situations. METHOD: The UTDallas Fearless steps Apollo data is comprised of 19,000 hours (A-11,A-13,A-1) possessing unique and multiple challenges as it is characterized by severe noise and degradation as well as overlap instances over the 30 channels. For our study, we have selected a subset of 100 hours manually transcribed by professional annotators for speaker labels. The 100 hours are obtained from three mission critical events: 1. Lift-Off (25 hours) 2. Lunar-Landing (50 hours) 3. Lunar-Walking (25 hours). Five channels of interest, out of 30 channels were selected with the most speech activity, the primary speakers operating these five channels are command/owners of these channels. For our analysis, we select five speaker roles: Flight Director (FD), Capsule Communicator (CAPCOM), Guidance, Navigation and, Control (GNC), Electrical, environmental, and consumables manager (EECOM), and Network (NTWK). To track and tag individual speakers across our Fearless Steps audio dataset, we use the concept of ‘where’s Waldo’ to identify all instances of our speakers-of-interest across a cluster of other speakers. Also, to understand speaker roles of our speaker-of-interests, we use speaker duration of primary speaker vs secondary speaker and speaker turns as our metrics to determine the role of the speaker and to understand their responsibility during the three critical phases of the mission. This enables a content linking capability as well as provide a pathway to analyzing group engagement, group dynamics of people working together in an enclosed space, psychological effects, and cognitive analysis in such individuals. IMPACT: NASA’s Apollo Program stands as one of the most significant contributions to humankind. This collection opens new research options for recognizing team communication, group dynamics, and human engagement/psychology for future deep space missions. Analyzing team communications to achieve such goals would allow for the formulation of educational and training technologies for assessment of STEM knowledge, task learning, and educational feedback. Also, identifying these personnel can help pay tribute and yield personal recognition to the hundreds of notable engineers and scientist who made this feat possible. ILLUSTRATION: In this work, we propose to illustrate how a pre-trained speech/language network can be used to obtain powerful speaker embeddings needed for speaker diarization. This framework is used to build these learned embeddings to label unique speakers over sustained audio streams. To train and test our system, we will make use of Fearless Steps Apollo corpus, allowing us to effectively leverage a limited label information resource (100 hours of labeled data out of +9000 hours). Furthermore, we use the concept of 'Finding Waldo' to identify key speakers of interest (SOI) throughout the Apollo-11 mission audio across multiple channel audio streams. 

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2. Historical Audio Search and Preservation: Finding Waldo Within the Fearless Steps Apollo 11 Naturalistic Audio Corpus

   https://doi.org/10.1109/MSP.2023.3237001  

   Chandra Shekar, Meena M. ; Hansen, John H.L. ( May 2023 , IEEE Signal Processing Magazine)

   Apollo 11 was the first manned space mission to successfully bring astronauts to the Moon and return them safely. As part of NASA’s goal in assessing team and mission success, all voice communications within mission control, astronauts, and support staff were captured using a multichannel analog system, which until recently had never been made available. More than 400 personnel served as mission specialists/support who communicated across 30 audio loops, resulting in 9,000+ h of data. It is essential to identify each speaker’s role during Apollo and analyze group communication to achieve a common goal. Manual annotation is costly, so this makes it necessary to determine robust speaker identification and tracking methods. In this study, a subset of 100hr derived from the collective 9,000hr of the Fearless Steps (FSteps) Apollo 11 audio data were investigated, corresponding to three critical mission phases: liftoff, lunar landing, and lunar walk. A speaker recognition assessment is performed on 140 speakers from a collective set of 183 NASA mission specialists who participated, based on sufficient training data obtained from 5 (out of 30) mission channels. We observe that SincNet performs the best in terms of accuracy and F score achieving 78.6% accuracy. Speaker models trained on specific phases are also compared with each other to determine if stress, g-force/atmospheric pressure, acoustic environments, etc., impact the robustness of the models. Higher performance was obtained using i-vector and x-vector systems for phases with limited data, such as liftoff and lunar walk. When provided with a sufficient amount of data (lunar landing phase), SincNet was shown to perform the best. This represents one of the first investigations on speaker recognition for massively large team-based communications involving naturalistic communication data. In addition, we use the concept of “Where’s Waldo?” to identify key speakers of interest (SOIs) and track them over the complete FSteps audio corpus. This additional task provides an opportunity for the research community to transition the FSteps collection as an educational resource while also serving as a tribute to the “heroes behind the heroes of Apollo.” 

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3. Understanding and Characterizing Speaker Roles within Naturalistic Task-Based Communications: The Fearless Steps APOLO-11 Corpus

   Chandra-Shekar, M. ; Hansen, J ( December 2022 , Acoustical Society of America (Fall Meeting))

   Naturalistic team based speech communications requires specific protocols/procedures to be followed to allow for effective task completion for distributed team members. NASA Apollo-11 was the first manned space mission to successfully bring astronauts to the moon and return them safely. Mission specialists roles within NASA Mission Control (MOCR) are complex and reflected in their communications. In this study, we perform speaker clustering to identify speech segments uttered by the same speaker from recently recovered Fearless Steps APOLLO corpus (CRSS-UTDallas). We propose a pretrained network to obtain speaker embeddings and use a framework that builds on these learned embeddings which achieves a clustering accuracy of 73.4%. We also track/tag key speakers-of-interest across three critical mission phases and analyze speaker roles based on speech duration. NASA communication protocols dictate that information be communicated in a concise manner. In automated communication analysis, individuals higher in trait dominance generally speak more and gain more control over group processes. Hence, speaker duration of primary- versus -secondary speaker and speaker turns are metrics used to determine speaker role. This analysis provides greater understanding of communications protocol and serves as a lasting tribute to the «Heroes Behind the Heroes of Apollo» as well as preserve “words spoken in space.” 

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4. Speaker Tracking using Graph Attention Networks with Varying Duration Utterances across Multi-Channel Naturalistic Data: Fearless Steps Apollo-11 Audio Corpus

   https://doi.org/10.21437/Interspeech.2023-1258  

   Shekar, Meena M. ; Hansen, John H. ( August 2023 , ISCA INTERSPEECH-2023)

   Speaker tracking in spontaneous naturalistic data continues to be a major research challenge, especially for short turn-taking communications. The NASA Apollo-11 space mission brought astronauts to the moon and back, where team based voice communications were captured. Building robust speaker classification models for this corpus has significant challenges due to variability of speaker turns, imbalanced speaker classes, and time-varying background noise/distortions. This study proposes a novel approach for speaker classification and tracking, utilizing a graph attention network framework that builds upon pretrained speaker embeddings. The model’s robustness is evaluated on a number of speakers (10-140), achieving classification accuracy of 90.78% for 10 speakers, and 79.86% for 140 speakers. Furthermore, a secondary investigation focused on tracking speakers-of-interest(SoI) during mission critical phases, essentially serves as a lasting tribute to the 'Heroes Behind the Heroes'. 

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5. FEARLESS STEPS: ADVANCEMENTS IN SPEECH TECHNOLOGY AND CORPUS DEVELOPMENT FOR NATURALISTIC AUDIO

   Joglekar, A. ; Hansen, J.H.L. ; Yousefi, M. ; Chandra Shekar, M. ; Chen, S.-J. ; Belitz, C. ( February 2023 , NASA Human Research Program Investigators Conference)

   INTRODUCTION: CRSS-UTDallas initiated and oversaw the efforts to recover APOLLO mission communications by re-engineering the NASA SoundScriber playback system, and digitizing 30-channel analog audio tapes – with the entire Apollo-11, Apollo-13, and Gemini-8 missions during 2011-17 [1,6]. This vast data resource was made publicly available along with supplemental speech & language technologies meta-data based on CRSS pipeline diarization transcripts and conversational speaker time-stamps for Apollo team at NASA Mission Control Center, [2,4]. In 2021, renewed efforts over the past year have resulted in the digitization of an additional +50,000hrs of audio from Apollo 7,8,9,10,12 missions, and remaining A-13 tapes. Cumulative digitization efforts have enabled the development of the largest publicly available speech data resource with unprompted, real conversations recorded in naturalistic environments. Deployment of this massive corpus has inspired multiple collaborative initiatives such as Web resources ExploreApollo (https://app.exploreapollo.org) LanguageARC (https://languagearc.com/projects/21) [3]. ExploreApollo.org serves as the visualization and play-back tool, and LanguageARC the crowd source subject content tagging resource developed by UG/Grad. Students, intended as an educational resource for k-12 students, and STEM/Apollo enthusiasts. Significant algorithmic advancements have included advanced deep learning models that are now able to improve automatic transcript generation quality, and even extract high level knowledge such as ID labels of topics being spoken across different mission stages. Efficient transcript generation and topic extraction tools for this naturalistic audio have wide applications including content archival and retrieval, speaker indexing, education, group dynamics and team cohesion analysis. Some of these applications have been deployed in our online portals to provide a more immersive experience for students and researchers. Continued worldwide outreach in the form of the Fearless Steps Challenges has proven successful with the most recent Phase-4 of the Challenge series. This challenge has motivated research in low level tasks such as speaker diarization and high level tasks like topic identification. IMPACT: Distribution and visualization of the Apollo audio corpus through the above mentioned online portals and Fearless Steps Challenges have produced significant impact as a STEM education resource for K-12 students as well as a SLT development resource with real-world applications for research organizations globally. The speech technologies developed by CRSS-UTDallas using the Fearless Steps Apollo corpus have improved previous benchmarks on multiple tasks [1, 5]. The continued initiative will extend the current digitization efforts to include over 150,000 hours of audio recorded during all Apollo missions. ILLUSTRATION: We will demonstrate WebExploreApollo and LanguageARC online portals with newly digitized audio playback in addition to improved SLT baseline systems, the results from ASR and Topic Identification systems which will include research performed on the corpus conversational. Performance analysis visualizations will also be illustrated. We will also display results from the past challenges and their state-of-the-art system improvements. 

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