rrbluke
Can the frequency-domain block-based AEC automatically handle single talk and double talk situations?
Hi, I think this is a remarkable job! I have a question about the frequency-domain block-based AEC. Is the AEC method you used able to handle the doubletalk case automatically? Or do you have to separate the far-end singletalk and doubletalk cases during pre-processing and manually stop the filter coefficient update during the doubletalk case?
Hi, I think this is a remarkable job! I have a question about the frequency-domain block-based AEC. Is the AEC method you used able to handle the doubletalk case automatically? Or do you have to separate the far-end singletalk and doubletalk cases during pre-processing and manually stop the filter coefficient update during the doubletalk case?
From generate_cache.py， I think linear AEC can automatically deal with single and double talk situations. Thank you for your project, it’s very useful for me!
Hi, I think this is a remarkable job! I have a question about the frequency-domain block-based AEC. Is the AEC method you used able to handle the doubletalk case automatically? Or do you have to separate the far-end singletalk and doubletalk cases during pre-processing and manually stop the filter coefficient update during the doubletalk case?
hello，I saw that the author used the train-hard folder under the AEC-Challenge dataset in the code, but I did not find this folder in this dataset, did you see it? could you please give me a reply,thanks very much!
The AEC does not need a VAD, as you can see from the implementation, and the paper being referenced there.
train_hard contains the hardest files from the dataset, which have been selected in terms of SNR.
it's so honored to receive your reply. i will read the code more carefully, thanks , best wishes !
train_hard contains the hardest files from the dataset, which have been selected in terms of SNR.
Excuse me, is this code complete？I didn't see any information about adding data to the train_hard folder (the train_hard folder is empty at first, that is, 0 pieces of data, which brought errors to the operation of the code). If is complete, could you please tell me where is it? I'm so sorry to disturb you. And hope that I can get your reply. Thanks very mush , Best wishes!
Hi, I think this is a remarkable job! I have a question about the frequency-domain block-based AEC. Is the AEC method you used able to handle the doubletalk case automatically? Or do you have to separate the far-end singletalk and doubletalk cases during pre-processing and manually stop the filter coefficient update during the doubletalk case?
From generate_cache.py， I think linear AEC can automatically deal with single and double talk situations. Thank you for your project, it’s very useful for me!
Hello, I'm so sorry to disturb you,from the generate_cache.py,I don't understand how linear AEC automatically deal with single and double talk situations.,can you tell me something about it?I'm looking forward to your reply.
