MicRank | Rank neural channel selection framework where a DNN

MicRank is a Python library. MicRank has no bugs, it has no vulnerabilities, it has build file available and it has low support. You can download it from GitHub.

MicRank is a Learning to Rank neural channel selection framework where a DNN is trained to rank microphone channels based on ASR-backend performance or any other metric/back-end task (e.g. STOI if one wishes to rank microphones based on speech intelligibility et cetera). It is agnostic with respect to the array geometry and type of recognition back-end and it does not require sample-level synchronization between devices. Remarkably, it is able to considerably improve over previous selection techniques, reaching comparable and in some instances better performance than oracle signal-based measures like PESQ, STOI or SDR. This is achieved with a very small model with only 266k learnable parameters, making this method much more computationally efficient than decoder or posterior based channel selection methods.