Trouble running tts example colab

[JRMeyer]

>>> guillaume.slize

5:41pm

Good Evening,

I am in the process of trying to finetune a tacotron model with a few
voice samples+ M-AI-Labs in French and I wanted to give a try at
training it with a classic dataset to see how it worked. slash
colab example
here
that describe how to train it with LJSpeech. slash
But somehow the script gives me an error saying it can't load the module
utils.io: No module named 'utils.io' . slash
I am not sure what I am doing wrong but would appreciate any pointers.

Thanks a lot,

[This is an archived TTS discussion thread from discourse.mozilla.org/t/trouble-running-tts-example-colab]

[JRMeyer]

>>> CrazyJoeDevola
[September 10, 2020, 2:38pm]

The examples all seem faulty. For me too. I guess the path to find the
utils.io is incorrect and should be changed to
something like TTS.utils.io or
TTS.tts.utils.io...depending on where you
are. IT can be seen as it's looking for a path where the dots are
representing what is normaly slash ' / slash '

[Archived Post]

[JRMeyer]

>>> guillaume.slize

4:00pm

Hi
[ slash CrazyJoeDevola](
TTS.utils.io did the tricks, encountering other
issues but now that I know that I need to modify the paths I will try to
resolve them. slash
Thanks for the tip, slash
Have a good day,

[Archived Post]

[JRMeyer]

>>> erogol
[September 10, 2020, 4:06pm]

colab examples should be used by their corresponding checkouts. I dont
thing in that case there would be a problem.

Otherwise feel free to contribute back your fix to the repo.

[Archived Post]

[JRMeyer]

>>> guillaume.slize

4:32pm

Hi, slash
Thanks for taking the time to answer. I don't have a background in
computer science so sometimes I am struggling understanding certain
terms, sorry about that. What exactly do you mean by 'corresponding
checkouts'?

[Archived Post]

[JRMeyer]

>>> erogol
[September 10, 2020, 5:13pm]

No problem
If you look at the code you see I checkout a certain version of the
repo. slash 'git checkout slash '. This updates the code to a certain version
which is compatible with the example code. Hope it clarifies.

[Archived Post]

[JRMeyer]

>>> guillaume.slize

8:37pm

Great! slash
I checked out from this hash: 7e799d5. I had to modify the losses.py
script (as explained
here)
and now it seems to run smoothly. slash
Thanks a lot. slash
Next step is using another dataset.

[Archived Post]

[JRMeyer]

>>> erogol
[September 11, 2020, 10:05am]

I've also released an small update which handles module name mismatch as
you use '''load_checkpoint''' function

[Archived Post]

[JRMeyer]

>>> guillaume.slize
[September 11, 2020, 7:03pm]

After using Ljspeech, I am trying to feed it another dataset, namely the
french part of mailabs. slash
I used preprocess.py to generate a nested list containing all the wav
files that I saved as a csv file using csv.writer

import numpy as np
import csv
from datasets.preprocess import mailabs
items= mailabs('/content/gdrive/My Drive/Tacotron/fr_FR')
with open('/content/gdrive/My Drive/Tacotron/fr_FR/metadata.csv', 'w', newline='') as csvfile:
writer = csv.writer(csvfile)
writer.writerows(items)

I then proceeded to split it into train and eval with this code:

shuf metadata.csv > metadata_shuf.csv
head -n 12000 metadata_shuf.csv > metadata_train.csv
tail -n 1100 metadata_shuf.csv > metadata_val.csv

Then I changed the path and name of the dataset in config.json

'datasets': [{'name': 'mailabs', 'path': '/content/gdrive/My Drive/Tacotron/fr_FR', 'meta_file_train': null, 'meta_file_val': null}]

But I keep getting the same error:

File '/usr/local/lib/python3.6/dist-packages/TTS-0.0.3+7e799d5-py3.6.egg/TTS/utils/generic_utils.py', line 78, in split_dataset
assert eval_split_size > 0, ' [!] You do not have enough samples to train. You need at least 100 samples.'
AssertionError: [!] You do not have enough samples to train. You need at least 100 samples.

However I have 31143 rows in my csv with valid wav files. slash
I am not sure where to look next, I am thinking it might have to do with
the order of the elements in the csv, but I am not sure.

I think you
successfully trained with the french part of the m-ai-labs dataset,
would you accept to share your process ?

EDIT: Nevermind, I realised that the preprocess was run inside the
train function, so it worked when I changed the regex in the preprocess
for mailabs to:

speaker_regex = re.compile('(male|female)/(?P<speaker_name>[^/]+)/')

[Archived Post]

[JRMeyer]

>>> kr6k3n
[September 20, 2020, 9:54am]

have you successfully trained the model in french?

[Archived Post]

[JRMeyer]

>>> guillaume.slize

10:14am

, slash
Yes, it worked for the mailabs, and the results were nice, but not the
fine-tuning I was hoping to do with my own dataset. I think it might
have to do with the quality

[Archived Post]

[JRMeyer]

>>> kr6k3n
[September 20, 2020, 10:55am]

Nice ! Would you mind sharing results?: I have been searching someone
like you for months since I can't afford any good gpu to train it on.
Otherwise I would totally understand.

[Archived Post]

[JRMeyer]

>>> julian.weber
[September 22, 2020, 1:39pm]

Yeah it was the regex that wasn't right for the french part of the
dataset like I said in this
issue
back in March. But maybe this is worth a PR

[Archived Post]