An informed separation algorithm based on sound field mapping for speech recognition systems
Dejan Markovic, Jigyasa Popat, Fabio Antonacci, Augusto Sarti, T. Kishore Kumar · 2016
This paper considers the problem of separation of speech sources from signals captured by a microphone array, and its impact on speech recognition systems. The proposed method improves the novel separation procedure based on processing of sound field maps in the ray space by incorporating the estimates of signal spectral envelopes into the design of the separation filter. In particular, we resort to a two-stage algorithm in which the assumptions regarding the signal spectral densities made in the first stage are replaced by their parametric estimates in the second stage. The performance gain is evaluated in real experiments and the impact on speech recognition accuracy is examined using several commercial cloud-based speech recognition APIs.