Comments (3)
Character and Mel-spectrogram have different lengths, len(character)< len(mel). In fast speech, we mapping from characters to mel so each character will represent for a chunk mel and length of this chunk, we call duration.
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I have a question: Can i use time alignment( duration in ms of each phoneme which is extracted by kaldi) for transform to duration format that you use for training fastspeech2?!
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@linhld0811 yes, but you should use the same phoneme in tts as you use in kalid.
check this: https://montreal-forced-aligner.readthedocs.io/
and this example file for ljspeech: https://github.com/ivanvovk/DurIAN/blob/master/filelists/train_filelist.txt
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Related Issues (20)
- Multi Speaker Training HOT 1
- Support Arabic Language HOT 2
- Tacotron2 Pre-training have difficulties
- Training Tacotron2 model became so slow after update HOT 1
- How do I get the RTF index HOT 1
- Japanese TTS model HOT 2
- Preprocessing error with ljspeech HOT 6
- tacotron2 parameter confusing, hop size configuration for databaker dataset is 256, not 300 HOT 1
- Installation on MacOS HOT 1
- Hifi-Gan config for Baker dataset HOT 1
- tensorflow-gpu==2.7.0 HOT 15
- Dose it support mutil speaker of chinese language ? HOT 1
- Android release as TTS engine HOT 7
- Train with another dataset HOT 2
- No module named 'tensorflow_tts' HOT 2
- Inference on MB MelGAN sounds great until testing on iOS HOT 3
- TensorFlowTTS support vietnamese HOT 2
- [MB_Melgan] Why is a model trained only generator is better than trained on both?
- support chinese HOT 2
- How to config CMakeLists.txt ? HOT 1
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