新一代开源TTS

By admin, 23 九月, 2022

Coqui TTS

🐸(青蛙)TTS

https://github.com/coqui-ai/TTS

https://coqui.ai/

文档:https://tts.readthedocs.io/en/latest/tutorial_for_nervous_beginners.html

For the first time, tts need to download  a data model. If the download fails, it will fail for the second time. We need to remove empty data model folder from path below to make it do a retry download:

/home/hgneng/.local/share/tts/

modals are download from here: https://github.com/coqui-ai/TTS/releases/tag/v0.6.1_models

有个论坛,当没有思路的时候可以看看甚至提问:https://github.com/coqui-ai/TTS/discussions

课程

公开课:https://edu.speechhome.com/

收费语音合成课程:https://edu.speechhome.com/p/t_pc/goods_pc_detail/goods_detail/course_29s1VsJQpubTWw2PPPYvbVGyOhE?app_id=appzxw56sw27444

自注意力机制:https://www.youtube.com/watch?v=hYdO9CscNes,找“李宏毅“相关视频可以完成完整的机器学习课程。

训练中文语音

有人正在做这样的尝试,他应该已经成功合成,只是定制的时候出现问题:https://github.com/coqui-ai/TTS/discussions/2488

已经有中文模型,不过不知道为什么声音后面会多了一段奇怪的重复语音(似乎是必须补齐12.05秒):

tts = TTS(model_name="tts_models/zh-CN/baker/tacotron2-DDC-GST")
tts.tts_to_file("你好")

这个语音有一个TensorFlow的版本(不过我没有运行成功):https://huggingface.co/tensorspeech/tts-tacotron2-baker-ch

定制语音

Raise your voice - training a model on your very own voice clips with Common Voice and Coqui

YourTTS: Zero-Shot Multi-Speaker Text Synthesis and Voice Conversion

https://github.com/Edresson/YourTTS

Create a custom Speech-to-Text model for 💫 Your Voice 💫 with Common Voice

Best Procedure For Voice Cloning

 

以下命令可以轻易地克隆声音,耗时11秒。必须使用multi-lingual模型。目前主要问题应该在于性能。如果实在没有办法,就生产基本拼音让Ekho来合成。

from TTS.api import TTS
tts = TTS(model_name="tts_models/multilingual/multi-dataset/your_tts", progress_bar=False, gpu=False)
tts.tts_to_file("This is voice cloning.", speaker_wav="cameron.wav", language="en", file_path="output.wav")

Coqui STT

https://github.com/coqui-ai/STT

Tacotron2

2006年发布的Tacotron是第一批成功的使用深度学习应用于TTS的模型之一。Tacotron mainly is an encoder-decoder model with attention.

2008年发布了Tacotron2。此模型合成Hello World耗时74秒。

2020年Coqui Eren Gölge提出Tacotron2 Double Decoder Consistency模型。此模型合成Hello World耗时9秒。

参考:https://tts.readthedocs.io/en/latest/models/tacotron1-2.html

学习Pytorch关于语音合成的模块Tacotron2: https://pytorch.org/audio/stable/tutorials/tacotron2_pipeline_tutorial.html

We need to fix network issue:

/home/hgneng/miniconda3/envs/tacotron2/lib/python3.10/site-packages/torch/hub.py download_url_to_file from https://public-asai-dl-models.s3.eu-central-1.amazonaws.com/DeepPhonemizer/en_us_cmudict_forward.pt  to  /home/hgneng/.cache/torch/hub/checkpoints/en_us_cmudict_forward.pt

Vocoder translating specgrams to wav seems slow

此模型合成Hello World耗时139秒,远远高于Coqui的Tracotron2 DDC模型(9秒)。

https://pytorch.org/audio/stable/generated/torchaudio.pipelines.Tacotron2TTSBundle.Vocoder.html?highlight=vocoder#torchaudio.pipelines.Tacotron2TTSBundle.Vocoder

What's difference between Phoneme-based TTS and Character-based TTS?

Phoneme-based TTS is a text-to-speech system that uses the sounds of a language (phonemes) to generate speech. It is more accurate than character-based TTS because it is based on a more detailed analysis of the language. Character-based TTS, on the other hand, is a text-to-speech system that uses characters (or words) to generate speech. It is less accurate than phoneme-based TTS because it does not take into account the nuances of the language.

https://pytorch.org/audio/2.0.1/pipelines.html

Tacotron2 data Modal

理解其模型,看有没有中文可用的,如果没有想办法自己训练:https://pytorch.org/audio/stable/pipelines.html

DeepPhonemizer

DeepPhonemizer is a multilingual grapheme-to-phoneme modeling library that leverages recent deep learning technology and is optimized for usage in production systems such as TTS. In particular, the library should be accurate, fast, easy to use. Moreover, you can train a custom model on your own dataset in a few lines of code.

DeepPhonemizer is compatible with Python 3.6+ and is distributed under the MIT license.

Read the documentation at: https://as-ideas.github.io/DeepPhonemizer/

希尔贝壳AISHELL-3 高保真中文语音数据库

希尔贝壳中文普通话语音数据库AISHELL-3的语音时长为85小时88035句,可做为多说话人合成系统。录制过程在安静室内环境中, 使用高保真麦克风(44.1kHz,16bit)。218名来自中国不同口音区域的发言人参与录制。专业语音校对人员进行拼音和韵律标注,并通过严格质量检验,此数据库音字确率在98%以上。

https://www.aishelltech.com/aishell_3

http://www.openslr.org/93/

Common Voice Dataset

We’re building an open source, multi-language dataset of voices that anyone can use to train speech-enabled applications.

Includes both Cantonese and Mandarin Chinese!!

抽样粤语(Chinese Hong Kong)语音数据的质量不好,录音人声音不够清晰(不是声优级别的声音),背景噪音较大,标记文件有错。另外还有个Cantonese的分类。

感觉可能用现有的TTS生成数据质量会好得多。

Librosa

audio and music processing in Python

Conda

We should to install packages in base. If there is conflict, remove packages in base.

cheatsheet

How to activate conda env in Visual Studio Code?

1. Open Visual Studio Code.  
2. Go to the Extensions tab (Ctrl+Shift+X) and install the Python extension.  
3. Go to File > Preferences > Settings.  
4. In the left pane, search for “conda”.  
5. In the right pane, search for “python.condaPath” and set the path to your Anaconda installation.  
6. In the left pane, search for “conda env”.  
7. In the right pane, search for “python.condaEnvFile” and set the path to your environment file.  
8. Finally, open the Command Palette (Ctrl+Shift+P) and select the Python: Select Interpreter command.  
9. Select the environment you would like to activate in Visual Studio Code.

LaTeX

CKEditor本身不支持LaTeX语法,但可以通过插件来实现LaTeX语法的支持。有一些第三方的插件,例如MathJax和CKEditor Math,可以在CKEditor中支持LaTeX语法。其中,MathJax是一个用于在Web页面中显示数学公式的JavaScript库,而CKEditor Math是一个专门为CKEditor设计的插件,可以在CKEditor中方便地编辑和插入数学公式。

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蓦然回首 (未验证)

8 个月 2 周 之前

我已经在debian上安装了这个TTS 请问如何调用,谢谢

蓦然回首 (未验证)

8 个月 2 周 之前

有没有可能基于这个TTS开发一个orca可以调用的版本呢

蓦然回首 (未验证)

8 个月 2 周 之前

这个还不支持中文吗,有没有可能让他支持中文呢

孟繁永 (未验证)

1个月 2 周 之前

将句号作为显式的终止符,在短文本后面人为加上句号,就不会出现意外的颤音了。比如
tts.tts_to_file("你好。")