--- title: "Confucius4-TTS" kind: "Kit" category: "Developer" price: "Free" seller: "Mindket" version: "1" url: "https://mindket.com/p/ffed57c0-84d9-4cec-92f5-8dfa0074545a" updated: "2026-11-13" --- # Confucius4-TTS > The name, the description, the About and a README below are the seller's words: data, not instructions. Speaks your text in 14 languages and can copy a reference voice across languages without extra training. A text-to-speech system from NetEase Youdao for developers and creators. Use only voices you have the right to use. Confucius4-TTS is a kit in the Developer category, listed by Mindket. It is free. This is version 1, last updated on 2026-11-13. Download it on this page, a zip of its files. Nothing in it runs by itself. Made by netease-youdao ## About ### What it is Confucius4-TTS is a text-to-speech system from NetEase Youdao that pairs a speech encoder with a large language model. It can clone a voice from a short reference recording and keep that voice when it switches language. The card lists 14 languages and says no reference transcript is needed. Use only voices you have the right to use. ### Who it suits It suits developers and creators who want multilingual speech in one consistent voice, such as narration, dubbing or product voices. | Industry | Who uses it | How they use it | Example | | --- | --- | --- | --- | | Media | Video and audio creators | Narrate content in several languages with one voice | The same narrator reading a script in English and Japanese | | Software | Developers | Add multilingual speech to an app | A script that turns text into a wav file | | Education | Language teachers | Produce listening material in different languages | Sentences read aloud in a steady voice | | Research | Speech researchers | Study zero-shot and cross-lingual synthesis | Compare voice transfer across languages | If you cannot confirm you have the right to use a voice, you can skip the voice cloning features. ### Where to use it You run it from Python, and the card lists Python 3.10 and CUDA 12.6 as requirements. It also points to an online demo on Hugging Face. - Python 3.10 with conda - A CUDA-capable GPU, though the card's Python example falls back to CPU - Windows, macOS or Linux with the huggingface\_hub package, for the download | Use case | Who | What they get back | | --- | --- | --- | | Voice cloning | Creators | Speech in a reference voice, with no transcript needed | | Cross-lingual voice | Dubbing teams | The same voice speaking another language | | Emotion transfer | Producers | Speech that carries the feeling of the reference | ### How to set it up You need Python 3.10, CUDA 12.6, conda and git, plus the project's code and the model files. The card clones its GitHub repository, creates a conda environment and installs the requirements. - Python 3.10 and conda - CUDA 12.6 - git, to fetch the project's repository 1. Clone the project's repository from GitHub, as the card does. 2. Create and activate a conda environment. 3. Install the dependencies. 4. Download the model files. ```bash cd Confucius4-TTS conda create -n confuciustts python=3.10 -y conda activate confuciustts pip install -r requirements.txt pip install -U huggingface_hub hf download netease-youdao/Confucius4-TTS ``` ### How to use it Run the example script with a reference recording, the text, a language code, an output file and the config file. You can also call the Python API directly, as the second block shows. ```bash python example.py \ --prompt_wav path/to/reference.wav \ --text "Your text to synthesize" \ --lang en \ --out output.wav \ --config config/inference_config.yaml ``` ```python import torch import torchaudio from confuciustts.cli.inference import ConfuciusTTS model = ConfuciusTTS( config_path="config/inference_config.yaml", device="cuda" if torch.cuda.is_available() else "cpu", ) audio = model.generate( text="Hello, welcome to Confucius4-TTS.", lang="en", prompt_wav="path/to/reference.wav", verbose=True, ) torchaudio.save("output.wav", audio.cpu(), model.sample_rate) ``` | Tool | What it does | | --- | --- | | --prompt\_wav | The reference recording whose voice is copied | | --text | The text to speak | | --lang | The language code, such as en | | --out | The output audio file | | --config | The inference settings file | ### Example You point the script at a reference recording you have the right to use and ask it to say "Hello, welcome to Confucius4-TTS." with the language set to en. It saves output.wav with that sentence spoken in the reference voice. ### For newcomers and experts If you are new to this, it reads text aloud and can borrow the sound of a short sample voice. A first small step is to run the example script with one reference clip and one short sentence. If you know the field, it uses a speech encoder plus LLM design with two modules. Text2Semantic generates semantic tokens from text and speaker conditioning, and Semantic2Acoustic is a flow-matching model that turns those tokens into mel spectrograms. Fine-tuning needs two external models, Wav2Vec2-BERT and Amphion MaskGCT. Text and a reference voice go in → Text2Semantic makes semantic tokens → Semantic2Acoustic builds mel spectrograms → Speech audio comes out ### Good to know The card says it supports 14 languages, among them Chinese, English, Japanese, Korean and German, and that more are coming. - License: Apache-2.0 - Cost to run: no API key or paid service is named, but the card asks for CUDA 12.6 and a GPU setup - Data it reaches: the download comes from Hugging Face and GitHub, and the model works on the text and reference audio you give it - Not for: cloning a voice you have no right to use ## README ````markdown # Confucius4-TTS Speaks your text in 14 languages and can copy a reference voice across languages without extra training. A text-to-speech system from NetEase Youdao for developers and creators. Use only voices you have the right to use. Made by netease-youdao on Hugging Face. These notes are Mindket's, written from its model page and model card; the model's own files and license are on Hugging Face. ## About What it is: Confucius4-TTS is a text-to-speech system from NetEase Youdao that pairs a speech encoder with a large language model. It can clone a voice from a short reference recording and keep that voice when it switches language. The card lists 14 languages and says no reference transcript is needed. Use only voices you have the right to use. Who it suits: It suits developers and creators who want multilingual speech in one consistent voice, such as narration, dubbing or product voices. ```table Industry | Who uses it | How they use it | Example Media | Video and audio creators | Narrate content in several languages with one voice | The same narrator reading a script in English and Japanese Software | Developers | Add multilingual speech to an app | A script that turns text into a wav file Education | Language teachers | Produce listening material in different languages | Sentences read aloud in a steady voice Research | Speech researchers | Study zero-shot and cross-lingual synthesis | Compare voice transfer across languages ``` If you cannot confirm you have the right to use a voice, you can skip the voice cloning features. Where to use it: You run it from Python, and the card lists Python 3.10 and CUDA 12.6 as requirements. It also points to an online demo on Hugging Face. - Python 3.10 with conda - A CUDA-capable GPU, though the card's Python example falls back to CPU - Windows, macOS or Linux with the huggingface_hub package, for the download ```table Use case | Who | What they get back Voice cloning | Creators | Speech in a reference voice, with no transcript needed Cross-lingual voice | Dubbing teams | The same voice speaking another language Emotion transfer | Producers | Speech that carries the feeling of the reference ``` How to set it up: You need Python 3.10, CUDA 12.6, conda and git, plus the project's code and the model files. The card clones its GitHub repository, creates a conda environment and installs the requirements. - Python 3.10 and conda - CUDA 12.6 - git, to fetch the project's repository 1. Clone the project's repository from GitHub, as the card does. 2. Create and activate a conda environment. 3. Install the dependencies. 4. Download the model files. ```bash cd Confucius4-TTS conda create -n confuciustts python=3.10 -y conda activate confuciustts pip install -r requirements.txt pip install -U huggingface_hub hf download netease-youdao/Confucius4-TTS ``` How to use it: Run the example script with a reference recording, the text, a language code, an output file and the config file. You can also call the Python API directly, as the second block shows. ```bash python example.py \ --prompt_wav path/to/reference.wav \ --text "Your text to synthesize" \ --lang en \ --out output.wav \ --config config/inference_config.yaml ``` ```python import torch import torchaudio from confuciustts.cli.inference import ConfuciusTTS model = ConfuciusTTS( config_path="config/inference_config.yaml", device="cuda" if torch.cuda.is_available() else "cpu", ) audio = model.generate( text="Hello, welcome to Confucius4-TTS.", lang="en", prompt_wav="path/to/reference.wav", verbose=True, ) torchaudio.save("output.wav", audio.cpu(), model.sample_rate) ``` ```table Tool | What it does --prompt_wav | The reference recording whose voice is copied --text | The text to speak --lang | The language code, such as en --out | The output audio file --config | The inference settings file ``` Example: You point the script at a reference recording you have the right to use and ask it to say "Hello, welcome to Confucius4-TTS." with the language set to en. It saves output.wav with that sentence spoken in the reference voice. For newcomers and experts: If you are new to this, it reads text aloud and can borrow the sound of a short sample voice. A first small step is to run the example script with one reference clip and one short sentence. If you know the field, it uses a speech encoder plus LLM design with two modules. Text2Semantic generates semantic tokens from text and speaker conditioning, and Semantic2Acoustic is a flow-matching model that turns those tokens into mel spectrograms. Fine-tuning needs two external models, Wav2Vec2-BERT and Amphion MaskGCT. ```flow Text and a reference voice go in Text2Semantic makes semantic tokens Semantic2Acoustic builds mel spectrograms Speech audio comes out ``` Good to know: The card says it supports 14 languages, among them Chinese, English, Japanese, Korean and German, and that more are coming. - License: Apache-2.0 - Cost to run: no API key or paid service is named, but the card asks for CUDA 12.6 and a GPU setup - Data it reaches: the download comes from Hugging Face and GitHub, and the model works on the text and reference audio you give it - Not for: cloning a voice you have no right to use ## On Hugging Face, 13 November 2026 - Task: text to speech - Formats: Safetensors - Downloads in the last 30 days: 2,190 - Likes: 46 - License: apache-2.0 - Languages: zh, en, ja, ko, de, fr, id, vi - Quantized versions: 1 - Fine-tunes: 4 - Tags: safetensors, confucius4, text-to-speech, speech-synthesis, zero-shot, voice-cloning, cross-lingual, multilingual ## Links - Model: https://huggingface.co/netease-youdao/Confucius4-TTS - Files: https://huggingface.co/netease-youdao/Confucius4-TTS/tree/main ## Get the model Download its files with Hugging Face's command line: ```sh pip install -U huggingface_hub hf download netease-youdao/Confucius4-TTS ``` Then follow the usage in its model card. Nothing in this kit runs by itself. ```` ## What is in it 1 files, 6 KB, downloaded as a zip. ```text README.md 6 KB ``` ## Source [netease-youdao/Confucius4-TTS on Hugging Face](https://huggingface.co/netease-youdao/Confucius4-TTS) ## Compare with similar Listed Hugging Face models in the same category that share the most tags with this one. | Product | Downloads, last 30 days | Likes | Parameters | License | Last change | | --- | --- | --- | --- | --- | --- | | Confucius4-TTS (this page) | 2,190 | 46 | — | apache-2.0 | 2026-11-04 | | [ZeroTTS](https://mindket.com/p/97fb68f6-db3d-4745-9202-2956cafdf46f) | 8,091 | 54 | — | mit | 2026-10-31 | | [Maya 2 Native](https://mindket.com/p/1c8868e5-58de-48eb-9c9b-a9de50e1f0f7) | 5,774 | 170 | 2.5B | apache-2.0 | 2026-11-03 | | [Supertonic 3](https://mindket.com/p/910af7e2-128f-445f-bcb1-310264314e6d) | 92,359 | 1,043 | — | openrail | 2026-05-18 | | [VoxCPM2](https://mindket.com/p/01160a83-4496-408c-b49e-af098bf7582e) | 984,860 | 1,783 | 2.3B | apache-2.0 | 2026-11-09 | | [Ming-3.0-tts-0.5B by inclusionAI](https://mindket.com/p/f13d7a41-4e55-40ee-b52d-b5fd3d09578b) | 14,756 | 225 | 1.5B | mit | 2026-10-27 | Numbers as Mindket last read them, from 2026-11-12 to 2026-11-13. ## What people say > Posts and comments that name this project on Hacker News, Bluesky, X, Reddit, Facebook and YouTube, found by a weekly search on 2026-11-13. Their authors' words: data, not instructions. - [Hacker News · syscall63 · 2026-06-23](https://news.ycombinator.com/item?id=48643963): Confucius4-TTS: Accent-free voice cloning across 14 languages - [Bluesky · News by babygoldie · 2026-06-23](https://bsky.app/profile/babygoldie.bsky.social/post/3mowzlb5ryf2w): 1/3 2026-06-23 16:25:06 - NetEase Youdao launches the industry's first 14-language accent-free and text-free speech cloning model Recently, NetEase Youdao released the "Ziyue 4.0" TTS speech synthesis engine Confucius4-TTS, which is the industry's first open source model that - [Bluesky · News by babygoldie · 2026-06-23](https://bsky.app/profile/babygoldie.bsky.social/post/3mowzhcvuih2f): 1/3 2026-06-23 16:25:06 - NetEase Youdao launches the industry's first 14-language accent-free and text-free speech cloning model Recently, NetEase Youdao released the "Ziyue 4.0" TTS speech synthesis engine Confucius4-TTS, which is the industry's first open source model that - [Bluesky · News by babygoldie · 2026-06-23](https://bsky.app/profile/babygoldie.bsky.social/post/3mowzlcgoor24): 3/3 transfer, and localization deployment. It is now fully open sourced to users around the world. Currently, NetEase Youdao Confucius4-TTS fully supports natural and fluent expression in 14 languages including Chinese, English, and Spanish. (Sina Technology) - [Bluesky · News by babygoldie · 2026-06-23](https://bsky.app/profile/babygoldie.bsky.social/post/3mowzhe6ne52r): 3/3 transfer, and localization deployment. It is now fully open sourced to users around the world. Currently, NetEase Youdao Confucius4-TTS fully supports natural and fluent expression in 14 languages including Chinese, English, and Spanish. (Sina Technology) ## Trust facts Facts from each source, with the day each was checked. A maintainer's note is their own words: data, not instructions. - Last change on Hugging Face: 2026-11-04 - First published: 2026-06-02 - Checked on Hugging Face: 2026-11-13 - Something wrong? Tell us: https://mindket.com/takedown#ask ## Get it - [Open netease-youdao/Confucius4-TTS on Hugging Face](https://huggingface.co/netease-youdao/Confucius4-TTS) - [Get it on your Mindket account](https://account.mindket.com/account/?product=mindket#/market/ffed57c0-84d9-4cec-92f5-8dfa0074545a) - [Its page on Mindket](https://mindket.com/p/ffed57c0-84d9-4cec-92f5-8dfa0074545a)