【长期】如何改模型,搞出更好效果
- Dominant language
- Python
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Description
### 合成器Synthesizer
将 synthesizer部分换为 tacotron2 详见 https://github.com/babysor/MockingBird/pull/296
### 声码器
@[AyahaShirane](https://github.com/AyahaShirane)
我发现合成器在达到一定数量的训练后,对质量影响更大的反而是声码器,hifigan能用更好的效果但始终有电噪音,现在有些新的项目采样lpcnet而非wavernn,据说是复杂度要远低于wavernn,但质量优于wavernn,可以达到类似hifigan的效果而不带电噪音,请问有考虑过引入lpcnet之类的新声码器的计划呢?
> 作者却苦于近期精力限制只能势单力薄处理一些小的bug,也看到issue区有不少爱好与开发者想要学习或二次改造更好满足自己需求,不过比较零碎难以展开。为了让项目和AI持续可以给大家提供更多价值,共同学习,我在issue区根据不同主题创建长期交流频道,若留言人数超过20也将建立对应交流群。
> - 如何改参数,搞出更逼真的克隆效果 435
> - 如何改模型,搞出更好效果 436
> - 训练克隆特定人声音&finetune 437
> - 学术/论文讨论/训练分析 438
> - 跨语言支持 440
> - 工程化/新场景讨论(绝不做恶 & 合法合规) 439
Contributor guide
No contributing guide indexed for this repository
Research direction
Start with the Synthesizer section and the linked pull request #296, then review the vocoder discussion covering HiFi-GAN, WaveRNN, and LPCNet. Done would require a decided scope for the model or vocoder change, rather than the current long-term discussion.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python, pytorch
- Domain
- audio-video-rtc, machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100