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ValueError: n must be at least one #368
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This caught me out for ages. Try including at least 32 wav files. I'm not sure why/where this is specified as a requirement. But I came across this in a youtube video that mentions this issue specifically. If you want to test immediately, you can just duplicate the existing files you have till there are 32. Obviously it won't make for a great model. But you'll confirm that you can proceed with training. EDIT: https://www.youtube.com/watch?v=ofe6IPjL8zg this is the video that mentions it. There is no visuals because the author is blind, as per their comments on the video. |
Thanks, @krones9000 I'll take a look. I'm trying to generate a Bulgarian voice and I'm not sure if cloning an EN voice is a good idea at all. I'd appreciate it if you have any thoughts to share about this. |
I'm afraid I'm still learning, so can't offer much advice in that regard. However, I do think you need to make sure that the language specified in the preprocessing matches the one you are trying to finetune from. So it may not allow you to finetune on and EN ckpt. From the TRAINING.md it gives the example of specifying en-us: python3 -m piper_train.preprocess I'm not sure what would happen if you specify en-us but then provide non en-us inputs. I have a feeling it will still work, but whether it works well is another question. |
No, it doesn't. I specified |
If you want to test the pipeline you can just copy paste your existing files to make duplicates till you have 32. Example, just using the first 3: wav/000.wav|male1|Одата Левски от цикъл Епопея на забравените на Иван Вазов. etc. At least with this you can verify the next steps work and then get better training files once you're sure it's possible to proceed. |
Thanks, I'll give it a try... |
same error... ;-( if this matter as it was build as per documentation
and
and metadata.csv as I may have an error that I missed somehow:
|
Ah, try removing the "wav/" prefix in the metadata. It is not required assuming you are giving a data directory where the csv and wav folder are both located and are providing: --dataset-format ljspeech in the preprocess. |
Are you specifying single speaker?: python3 -m piper_train.preprocess If so, I don't think it expects a speaker column. Sorry, just running through possible ideas now. |
yes, here is the command:
Removed speaker column, but the error persists ;-( |
I'm afraid I'm all out of ideas. It could be a mismatch between the model and the training data that we're not seeing. Can you link the hugginface link for the model you're trying to finetune on? |
Sorry for the late reply. I'm following the training (https://github.com/rhasspy/piper/blob/master/TRAINING.md) documentation on my local machine, not using huggingface. At I point when I have some free time I'll dig deeper. Hopefully, there will be more fresh ideas here at a point. |
yeah i tried to train my own audio i had same problem. |
I have fixed problem on csv and added 1 parameter Why 2 same text on one column. Also if you so much cpu cores.You need to add parameter |
thanks @eix128. Could you explain this in more detail, please:
which of these is text and which one pronunciation:
And finally, doesn't the pronunciation come from the wav file? |
no , for example on old english. so: this is not so important for this project but some projects requires it. |
Good catch. My dataset has smaller but long samples, so I set num workers to 1 and it worked just fine. I think it wouldn't divide correctly with any higher |
Well , piper should also allow 1 pipe too. |
check out this article for the error:
setting
has solved it for some |
Hello there,
Following the instructions in Training.md
those commands had been used as described in the file in the cloned piper local folder:
I got the following error executing the
preprocess
command:the metadata.csv is (the text is Cyrillic - Bulgarian):
metadata.csv is in /Projects/TTS/test/:
I'll appreciate any comments/help.
Thank you
Ivo
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