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In this paper, we present an ego noise reduction method for a hose-shaped rescue robot developed for search and rescue operations in large-scale disasters such as a massive earthquake. It can enter narrow and dark places covered with rubble in a disaster site and is used to search for disaster victims by capturing their voices with its microphone array. However, ego noises, such as vibration or fricative sounds, are mixed with the voices, and it is difficult to differentiate them from a call for help from a disaster victim. To solve this problem, we here propose a two-step noise reduction method as follows: (1) the estimation of both speech and ego noise signals from an observed multichannel signal by multichannel nonnegative matrix factorization (NMF) with the rank-1 spatial constraint, which was proposed by Kitamura et al., and (2) the application of noise cancellation to the estimated speech signal using the noise reference. Our evaluations show that this approach is effective for suppressing ego noise.

Rescue robots have been developed for search and rescue operations in times of large-scale disasters. Such a robot is used to search for survivors in disaster sites by capturing their voices with its microphone array. However, since the robot has many vibration motors, ego noise is mixed with voices, and it is difficult to differentiate the ego noise from a call for help from a disaster survivor. In our previous works, an ego noise reduction technique that combines a method of blind source separation called independent low-rank matrix analysis and postprocessing for noise cancellation was proposed. In the practical use of this robot, to determine the precise location of survivors, the direction of the observed voice should be estimated after the ego noise reduction process. To achieve this objective, in this study, a new hose-shaped rescue robot with microphone arrays was developed. Moreover, we adapt postfilter called MOSIE to our previous noise reduction method to listen to stereo sound because this robot can record stereo sound. By performing in a simulated disaster site, we confirm that the operator can perceive the direction of a survivor's location by applying a speech enhancement technique combining independent low-rank matrix analysis, noise cancellation, and postfiltering to the observed multichannel noisy signals.