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thanks for such a great work, in DNS challenge, personalized speech enhancement is gradually replaced the non-personalized speech enhancement, this is a challenge and interesting task, since it need to use speaker recognition model to extract speaker embedding, which is already existed in We-Speaker
The text was updated successfully, but these errors were encountered:
Also with Esspresif's laterial thought on BSS you could replace the KWS on each signal output with VAD that maybe uses ondevice training of a smaller model to bias to a voice profile?
VAD can often be lighter than KWS and maybe post process KWS or upstream.
I agree totally that extraction of a known than cancellation of the unknown seems to be the way forward and the above paper seems the only alternative to Googles VoiceFilterLite (Please opensource :) ) so that it can run downstream on lite hardware or concurrent multiple instances.
thanks for such a great work, in DNS challenge, personalized speech enhancement is gradually replaced the non-personalized speech enhancement, this is a challenge and interesting task, since it need to use speaker recognition model to extract speaker embedding, which is already existed in We-Speaker
The text was updated successfully, but these errors were encountered: