Comments (8)
Hi~
Alignment information was obtained using a tacorton2 or transformer model,
but it has been removed from git. Could you please tell me why?
As you know, alignment information is required to use a DB other than ljspeech.
I didn't spend time writing a note about how to extract alignment from Tacotron2, so I remove it from new commit.
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@xcmyz 请问一下中文音频的alignment如何获取npy信息呢???请赐教
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@xcmyz 请问一下中文音频的alignment如何获取npy信息呢???请赐教
通过强制对齐工具获取音频和音素的对齐。
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@xcmyz 我这边已经对齐过了,通过kaldi,但是npy是怎么生成的,我看是用tensorflow版本的tacotron2生成的吗?是training_data里的吗?
from fastspeech.
@xcmyz 我这边已经对齐过了,通过kaldi,但是npy是怎么生成的,我看是用tensorflow版本的tacotron2生成的吗?是training_data里的吗?
我用nvidia版本的tacotron2或者每一个character对应的mel谱的帧。
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嗯嗯,谢谢,请问这个npy是再tensorflow版本的tacotron2的training_data里吗?是audio 还是linear 还是mels里面,这个困惑我好久了,谢谢!!
from fastspeech.
嗯嗯,谢谢,请问这个npy是再tensorflow版本的tacotron2的training_data里吗?是audio 还是linear 还是mels里面,这个困惑我好久了,谢谢!!
我是通过tacotron2的模型中提取的,比方说:
- nvidia tacotron2的模型输入时character,输出是mel spectrogram;
- tacotron2中location sensitive attention会输出一个矩阵(shape:[length_mel, length_character])
- 上面这个矩阵包含了每个character和mel spectrogram的对齐(每一个character的attention到哪一个帧的mel spectrogram)
我这里的duration即为每个character对应的帧长度,比如[h, a, t]的duration就是[2, 3, 4]。(我用的是pytorch版本的nvidia tacotron2)
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好的好的,谢谢,不胜感激!
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Related Issues (20)
- Is this still maintained?
- training stops in few seconds and no checkpoint file created HOT 3
- error in new commit HOT 9
- Preprocess.py got stuck: Tried to debug
- Have anyone tried using LSTM to replace FFT block?
- What is the difference between postnet and CBHG? HOT 3
- 请问训练多久得到的pretrain model呢?然后,请问使用了多少GPU呢? HOT 1
- Resume training from checkpoint result in NaN? HOT 1
- How to extract alignment from tacotron2? HOT 6
- long int 转换成float erro
- denoiser HOT 1
- some question about squeezewave denoiser
- onnxruntime.capi.onnxruntime_pybind11_state.Fail: [ONNXRuntimeError] : 1 : FAIL : Load model from fastwave.onnx failed:Type Error: Type parameter (T) bound to different types (tensor(double) and tensor(float) in node ().
- Expected object of backend CUDA but got backend CPU for argument #3 'index' HOT 1
- duration loss calulated in log domain or linear domain
- wav in chinese HOT 1
- Error when training new model for another language
- BUG:OSError: sndfile library not found HOT 1
- RuntimeError: stack expects each tensor to be equal size, but got [40, 240] at entry 0 and [78, 202] at entry 1
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