Speech activity detection for NASA apollo space missions: challenges and solutions
Ali Ziaei, Lakshmish Kaushik, Abhijeet Sangwan, John H. L. Hansen, Douglas W. Oard · 2014
Speech Activity Detection(SAD) is a well researched problem for communication, command and control applications, where audio segments are short duration and solution proposed for noisy as well as clean environments. In this study, we inves-tigate the SAD problem using NASA’s Apollo space mission data [1]. Unlike traditional speech corpora, the audio recordings in Apollo are extensive from a longitudinal perspective (i.e., 6-12 days each). From SAD perspective, the data offers many challenges: (i) noise distortion with variable SNR, (ii) chan-nel distortion, and (iii) extended periods of non-speech activity. Here, we use the recently proposed Combo-SAD, which has performed remarkably well in DARPA RATS evaluations, as our baseline system [2]. Our analysis reveals that the Combo-SAD performs well when speech-pause durations are balanced in the audio segment, but deteriorates significantly when speech is sparse or absent. In order to mitigate this problem, we pro-pose a simple yet efficient technique which builds an alternative model of speech using data from a separate corpora, and em-beds this new information within the Combo-SAD framework. Our experiments show that the proposed approach has a major impact on SAD performance (i.e., +30 % absolute), especially in audio segments that contain sparse or no speech information.