# Finetune your own AM based on FastSpeech2 with AISHELL-3.
This example shows how to finetune your own AM based on FastSpeech2 with AISHELL-3. We use part of csmsc's data (top 200) as finetune data in this example. The example is implemented according to this [discussion](https://github.com/PaddlePaddle/PaddleSpeech/discussions/1842). Thanks to the developer for the idea.
We use AISHELL-3 to train a multi-speaker fastspeech2 model here. You can refer [examples/aishell3/tts3](https://github.com/lym0302/PaddleSpeech/tree/develop/examples/aishell3/tts3) to train multi-speaker fastspeech2 from scratch.
We use AISHELL-3 to train a multi-speaker fastspeech2 model. You can refer [examples/aishell3/tts3](https://github.com/lym0302/PaddleSpeech/tree/develop/examples/aishell3/tts3) to train multi-speaker fastspeech2 from scratch.
## Prepare
### Download Pretrained Fastspeech2 model
@ -211,4 +211,4 @@ optional arguments:
8. `--ngpu` is the number of gpus to use, if ngpu == 0, use cpu.
### Tips
If you want to get better audio quality, you can use more audios to finetune.
If you want to get better audio quality, you can use more audios to finetune.