Comments (3)
Hello, firelex. To add to my previous comments in #22, NNSVS makes use of sinsy[1] via pysinsy[2] to convert musicxml files to HTS full-context label files, and currently it supports Japanese only. I have the forked version of sinsy[3] which supports English and Chinese(Chinese support is imported from Sinsy-Remix[4]), but I have not fully tested it yet. If you are interested, please see my forked version of sinsy.
- http://www.sinsy.jp/
- https://github.com/r9y9/pysinsy
- https://github.com/taroushirani/sinsy/tree/m17n_dev
- https://github.com/hyperzlib/Sinsy-Remix
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I am currently working on other priority items (e.g. #15) so I cannot guarantee how soon I will work on preparing the instructions. In the meantime, please check the thread #22 (comment).
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Super, very helpful. I'll give this a try. I've used Gentle for forced alignment so far, will evaluate it against the sinsy fork!
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Related Issues (20)
- train_acoustic entry point missing from setup.py HOT 2
- Add DiffSinger configurations and recipes to reproduce experiments reported in NNSVS documentation HOT 6
- Diffusion-based acoustic models HOT 2
- from nnsvs.train_util import NpyFileSource HOT 1
- The combination of NPSSMDNMultistreamParametricModel and BiLSTMResF0NonAttentiveDecoder with use_mdn=True results in training failure HOT 4
- [suggeston] Add an warning for acoustic model config not matching feature generation
- Converting Enunu to NNSVS HOT 3
- A Question HOT 1
- Refactor svs.py to be more modular and extensible for ENUNU
- Remove the trainable post-filter functionality to make code simple
- A separate training script for F0 prediction model HOT 1
- Can nnsvs be run on AMD GPUs via ROCm? HOT 2
- Using Enunu english model on NNSVS HOT 3
- AttributeError: module 'matplotlib' has no attribute 'axes'
- Is it unnecessary to resample the audio which is not 48k to 48k? HOT 2
- !pip install nnsvs HOT 6
- Cannot install nnsvs HOT 2
- (suggestion) Ability to preface Gaussian Diffusion with a user-selectable acoustic model
- ModuleNotFoundError("No module named 'nnsvs.transformer'") HOT 1
- Adapting a dataset to nnsvs format
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