# 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
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@@ -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.
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If you want to get better audio quality, you can use more audios to finetune.
