Enhanced Robot Audition Based on Microphone Array Source Separation with Post-Filter
This work addresses sound source separation for mobile robots, enabling better auditory perception in noisy environments, but it appears incremental as it builds on existing methods with specific adaptations.
The paper tackles the problem of separating simultaneous sound sources for mobile robots using a microphone array with Geometric Source Separation and a post-filter, achieving reductions in log spectral distortion and increases in signal-to-noise ratio of about 10 dB and 14 dB for three interfering speakers with noise.
We propose a system that gives a mobile robot the ability to separate simultaneous sound sources. A microphone array is used along with a real-time dedicated implementation of Geometric Source Separation and a post-filter that gives us a further reduction of interferences from other sources. We present results and comparisons for separation of multiple non-stationary speech sources combined with noise sources. The main advantage of our approach for mobile robots resides in the fact that both the frequency-domain Geometric Source Separation algorithm and the post-filter are able to adapt rapidly to new sources and non-stationarity. Separation results are presented for three simultaneous interfering speakers in the presence of noise. A reduction of log spectral distortion (LSD) and increase of signal-to-noise ratio (SNR) of approximately 10 dB and 14 dB are observed.