Mitu is a girl vocal supporting the singing RVC model
Inference Comparison
After Inference
Model Introduction
When training Mi Tu, I was surprised that 20% of his tone leaned toward Xiao Tuantuan's voice.
Miaoyin collected 20 minutes of dry notes and about 15 minutes of singing to generate the MiTu model. From a reasoning perspective, this model can be rated A+ in all aspects.
Next, I will reason about the performance and the singing parts through several different timbres.
By the way, I'll answer questions I've answered one by one below for friends who have encountered problems using models these days.
Original sound
<!--[if lt IE 9]>document.createElement('audio');<![endif]-->After reasoning
Original sound
After reasoning
From the above reasoning, you should be able to tell that different original voices produce different inference effects, but the tone tone remains similar. So when using this kind of unspecified model, if you feel the effect is not great or differs from Miaoyin Workshop's reasoning, try to use the effect of mimicking the tone. Of course, if you really can't solve the problem, you can upload the original audio to a cloud drive and send me a private message on the site. I will solve it for you during my free time.
Singing portion performance
Parameters
Tone change: 0
Algorithm: rmvpe
Training: 200
Sampling rate: 44K
Training log
![Image[1]-Miaoyin-RVC Tone Model Workshop](https://apis.klrvc.com/wp-content/uploads/2024/06/20240630144909331-WX20240630-144723-300x177.png)
I will also package the npy file into the compressed file. Although I don't need the npy file now, it still helps a lot for some older versions of the RVC main program.
Miaoyin model
Version Details
Recommended Parameters
Related Models
Keywords
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