2015/09/23 by Hendrik Barfuss, Barfuss, Hendrik, Christian Huemmer +5 · 1 citation
Computer Science · #Blind Source Separation Techniques #FOS: Computer and information sciences #Sound (cs.SD) #Speech Recognition and Synthesis #Speech and Audio Processing #cs.SD
paper · pdf · doi:10.48550/arxiv.1509.06882
arxiv created 2015/09/23 · openalex publication_date 2015/09/23 · arxiv updated 2015/09/24 · openalex created_date 2016/06/24 · openalex updated_date 2026/07/28
In this contribution to the 3rd CHiME Speech Separation and Recognition Challenge (CHiME-3) we extend the acoustic front-end of the CHiME-3 baseline speech recognition system by a coherence-based Wiener filter which is applied to the output signal of the baseline beamformer. To compute the time- and frequency-dependent postfilter gains the ratio between direct and diffuse signal components at the output of the baseline beamformer is estimated and used as approximation of the short-time signal-to-noise ratio. The proposed spectral enhancement technique is evaluated with respect to word error rates of the CHiME-3 challenge baseline speech recognition system using real speech recorded in public environments. Results confirm the effectiveness of the coherence-based postfilter when integrated into the front-end signal enhancement.