diff --git a/.gitattributes b/.gitattributes
index a6344aac8c09253b3b630fb776ae94478aa0275b..81b128a0b5e4c91dc191dd07e483f7a35dd0d555 100644
--- a/.gitattributes
+++ b/.gitattributes
@@ -33,3 +33,34 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
*.zip filter=lfs diff=lfs merge=lfs -text
*.zst filter=lfs diff=lfs merge=lfs -text
*tfevents* filter=lfs diff=lfs merge=lfs -text
+VoxCPM/assets/voxcpm_model.png filter=lfs diff=lfs merge=lfs -text
+VoxCPM/ckpts/assets/voxcpm_model.png filter=lfs diff=lfs merge=lfs -text
+VoxCPM/examples/example.wav filter=lfs diff=lfs merge=lfs -text
+VoxCPM/prompt_sample.wav filter=lfs diff=lfs merge=lfs -text
+eval/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/asr_example_hotword.wav filter=lfs diff=lfs merge=lfs -text
+eval/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/example/asr_example.wav filter=lfs diff=lfs merge=lfs -text
+eval/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/fig/res.png filter=lfs diff=lfs merge=lfs -text
+eval/speech_seaco_paraformer_large_asr_nat-zh-cn-16k-common-vocab8404-pytorch/fig/seaco.png filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/UniSpeech-SAT/UniSpeech_SAT_SUPERB_Results.png filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/WavLM/WavLM_ASR.PNG filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/WavLM/WavLM_SUPERB_Leaderboard.png filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/WavLM/WavLM_SUPERB_Results.png filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/David_Faustino/hn8GyCJIfLM_0000012.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/David_Faustino/xTOk1Jz-F_g_0000015.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/Josh_Gad/HXUqYaOwrxA_0000015.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/Josh_Gad/RFyw7V3SOnQ_0000001.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/Lea_Thompson/HladKGyKTLM_0000006.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/Lea_Thompson/mHTAr5dlAgc_0000004.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/Zulay_Henao/WbB8m9-wlIQ_0000001.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/downstreams/speaker_verification/vox1_data/Zulay_Henao/gFfcgOVmiO0_0000002.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/David_Faustino/hn8GyCJIfLM_0000012.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/David_Faustino/xTOk1Jz-F_g_0000015.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/Josh_Gad/HXUqYaOwrxA_0000015.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/Josh_Gad/RFyw7V3SOnQ_0000001.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/Lea_Thompson/HladKGyKTLM_0000006.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/Lea_Thompson/mHTAr5dlAgc_0000004.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/Zulay_Henao/WbB8m9-wlIQ_0000001.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/examples/speaker_verification/vox1_data/Zulay_Henao/gFfcgOVmiO0_0000002.wav filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/fairseq/data/data_utils_fast.cpython-36m-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text
+eval/thirdparty/UniSpeech/src/fairseq/data/data_utils_fast.cpython-37m-x86_64-linux-gnu.so filter=lfs diff=lfs merge=lfs -text
+实验三：基于VoxCPM的音色克隆（实验指导）.pdf filter=lfs diff=lfs merge=lfs -text
diff --git a/VoxCPM/.github/workflows/publish-to-pypi.yml b/VoxCPM/.github/workflows/publish-to-pypi.yml
new file mode 100644
index 0000000000000000000000000000000000000000..fd658ce76de2161fd6cda7d5f9d3380a263f9f22
--- /dev/null
+++ b/VoxCPM/.github/workflows/publish-to-pypi.yml
@@ -0,0 +1,54 @@
+name: Publish Python 🐍 distribution 📦 to PyPI
+
+on:
+ release:
+ types: [created]
+
+jobs:
+ build:
+ name: Build distribution 📦
+ runs-on: ubuntu-latest
+
+ steps:
+ - uses: actions/checkout@v4
+ with:
+ persist-credentials: false
+ - name: Set up Python
+ uses: actions/setup-python@v5
+ with:
+ python-version: "3.x"
+ - name: Install pypa/build
+ run: >-
+ python3 -m
+ pip install
+ build
+ --user
+ - name: Build a binary wheel and a source tarball
+ run: python3 -m build
+ - name: Store the distribution packages
+ uses: actions/upload-artifact@v4
+ with:
+ name: python-package-distributions
+ path: dist/
+
+ publish-to-pypi:
+ name: >-
+ Publish Python 🐍 distribution 📦 to PyPI
+ if: startsWith(github.ref, 'refs/tags/') # only publish to PyPI on tag pushes
+ needs:
+ - build
+ runs-on: ubuntu-latest
+ environment:
+ name: pypi
+ url: https://pypi.org/p/voxcpm
+ permissions:
+ id-token: write
+
+ steps:
+ - name: Download all the dists
+ uses: actions/download-artifact@v4
+ with:
+ name: python-package-distributions
+ path: dist/
+ - name: Publish distribution 📦 to PyPI
+ uses: pypa/gh-action-pypi-publish@release/v1
diff --git a/VoxCPM/.gitignore b/VoxCPM/.gitignore
new file mode 100644
index 0000000000000000000000000000000000000000..f685e73ffb42e09c1df390cb5f77f22a04967e07
--- /dev/null
+++ b/VoxCPM/.gitignore
@@ -0,0 +1,3 @@
+launch.json
+__pycache__
+voxcpm.egg-info
\ No newline at end of file
diff --git a/VoxCPM/LICENSE b/VoxCPM/LICENSE
new file mode 100644
index 0000000000000000000000000000000000000000..abd7fd66f359b65b3f65c9b495f24a5120e9b98e
--- /dev/null
+++ b/VoxCPM/LICENSE
@@ -0,0 +1,201 @@
+Apache License
+ Version 2.0, January 2004
+ http://www.apache.org/licenses/
+
+ TERMS AND CONDITIONS FOR USE, REPRODUCTION, AND DISTRIBUTION
+
+ 1. Definitions.
+
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+ meet the following conditions:
+
+ (a) You must give any other recipients of the Work or
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+
+ (b) You must cause any modified files to carry prominent notices
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+
+ (c) You must retain, in the Source form of any Derivative Works
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+ You may add Your own copyright statement to Your modifications and
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+ for use, reproduction, or distribution of Your modifications, or
+ for any such Derivative Works as a whole, provided Your use,
+ reproduction, and distribution of the Work otherwise complies with
+ the conditions stated in this License.
+
+ 5. Submission of Contributions. Unless You explicitly state otherwise,
+ any Contribution intentionally submitted for inclusion in the Work
+ by You to the Licensor shall be under the terms and conditions of
+ this License, without any additional terms or conditions.
+ Notwithstanding the above, nothing herein shall supersede or modify
+ the terms of any separate license agreement you may have executed
+ with Licensor regarding such Contributions.
+
+ 6. Trademarks. This License does not grant permission to use the trade
+ names, trademarks, service marks, or product names of the Licensor,
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+ origin of the Work and reproducing the content of the NOTICE file.
+
+ 7. Disclaimer of Warranty. Unless required by applicable law or
+ agreed to in writing, Licensor provides the Work (and each
+ Contributor provides its Contributions) on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or
+ implied, including, without limitation, any warranties or conditions
+ of TITLE, NON-INFRINGEMENT, MERCHANTABILITY, or FITNESS FOR A
+ PARTICULAR PURPOSE. You are solely responsible for determining the
+ appropriateness of using or redistributing the Work and assume any
+ risks associated with Your exercise of permissions under this License.
+
+ 8. Limitation of Liability. In no event and under no legal theory,
+ whether in tort (including negligence), contract, or otherwise,
+ unless required by applicable law (such as deliberate and grossly
+ negligent acts) or agreed to in writing, shall any Contributor be
+ liable to You for damages, including any direct, indirect, special,
+ incidental, or consequential damages of any character arising as a
+ result of this License or out of the use or inability to use the
+ Work (including but not limited to damages for loss of goodwill,
+ work stoppage, computer failure or malfunction, or any and all
+ other commercial damages or losses), even if such Contributor
+ has been advised of the possibility of such damages.
+
+ 9. Accepting Warranty or Additional Liability. While redistributing
+ the Work or Derivative Works thereof, You may choose to offer,
+ and charge a fee for, acceptance of support, warranty, indemnity,
+ or other liability obligations and/or rights consistent with this
+ License. However, in accepting such obligations, You may act only
+ on Your own behalf and on Your sole responsibility, not on behalf
+ of any other Contributor, and only if You agree to indemnify,
+ defend, and hold each Contributor harmless for any liability
+ incurred by, or claims asserted against, such Contributor by reason
+ of your accepting any such warranty or additional liability.
+
+ END OF TERMS AND CONDITIONS
+
+ APPENDIX: How to apply the Apache License to your work.
+
+ To apply the Apache License to your work, attach the following
+ boilerplate notice, with the fields enclosed by brackets "[]"
+ replaced with your own identifying information. (Don't include
+ the brackets!) The text should be enclosed in the appropriate
+ comment syntax for the file format. We also recommend that a
+ file or class name and description of purpose be included on the
+ same "printed page" as the copyright notice for easier
+ identification within third-party archives.
+
+ Copyright OpenBMB
+
+ Licensed under the Apache License, Version 2.0 (the "License");
+ you may not use this file except in compliance with the License.
+ You may obtain a copy of the License at
+
+ http://www.apache.org/licenses/LICENSE-2.0
+
+ Unless required by applicable law or agreed to in writing, software
+ distributed under the License is distributed on an "AS IS" BASIS,
+ WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ See the License for the specific language governing permissions and
+ limitations under the License.
\ No newline at end of file
diff --git a/VoxCPM/README.md b/VoxCPM/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..93d32a1c575d8f796f9bc307aa4461b0c9bb2acc
--- /dev/null
+++ b/VoxCPM/README.md
@@ -0,0 +1,353 @@
+## 🎙️ VoxCPM: Tokenizer-Free TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning
+
+
+[](https://github.com/OpenBMB/VoxCPM/) [](https://arxiv.org/abs/2509.24650) [](https://huggingface.co/openbmb/VoxCPM-0.5B) [](https://modelscope.cn/models/OpenBMB/VoxCPM-0.5B) [](https://huggingface.co/spaces/OpenBMB/VoxCPM-Demo) [](https://openbmb.github.io/VoxCPM-demopage)
+
+
+
+
+
+
+
+👋 Contact us on [WeChat](assets/wechat.png)
+
+
+
+## News
+* [2025.09.30] 🔥 🔥 🔥 We Release VoxCPM [Technical Report](https://arxiv.org/abs/2509.24650)!
+* [2025.09.16] 🔥 🔥 🔥 We Open Source the VoxCPM-0.5B [weights](https://huggingface.co/openbmb/VoxCPM-0.5B)!
+* [2025.09.16] 🎉 🎉 🎉 We Provide the [Gradio PlayGround](https://huggingface.co/spaces/OpenBMB/VoxCPM-Demo) for VoxCPM-0.5B, try it now!
+
+## Overview
+
+VoxCPM is a novel tokenizer-free Text-to-Speech (TTS) system that redefines realism in speech synthesis. By modeling speech in a continuous space, it overcomes the limitations of discrete tokenization and enables two flagship capabilities: context-aware speech generation and true-to-life zero-shot voice cloning.
+
+Unlike mainstream approaches that convert speech to discrete tokens, VoxCPM uses an end-to-end diffusion autoregressive architecture that directly generates continuous speech representations from text. Built on [MiniCPM-4](https://huggingface.co/openbmb/MiniCPM4-0.5B) backbone, it achieves implicit semantic-acoustic decoupling through hierachical language modeling and FSQ constraints, greatly enhancing both expressiveness and generation stability.
+
+
+
+
[ModelBest](https://modelbest.cn/)
+
+- 
[THUHCSI](https://github.com/thuhcsi)
+
+
+## ⭐ Star History
+ [](https://star-history.com/#OpenBMB/VoxCPM&Date)
+
+
+## 📚 Citation
+
+If you find our model helpful, please consider citing our projects 📝 and staring us ⭐️！
+
+```bib
+@article{voxcpm2025,
+ title = {VoxCPM: Tokenizer-Free TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning},
+ author = {Zhou, Yixuan and Zeng, Guoyang and Liu, Xin and Li, Xiang and Yu, Renjie and Wang, Ziyang and Ye, Runchuan and Sun, Weiyue and Gui, Jiancheng and Li, Kehan and Wu, Zhiyong and Liu, Zhiyuan},
+ journal = {arXiv preprint arXiv:2509.24650},
+ year = {2025},
+}
+```
diff --git a/VoxCPM/app.py b/VoxCPM/app.py
new file mode 100644
index 0000000000000000000000000000000000000000..cbe163a06e14f32a54693d08ffb99120e0c95b97
--- /dev/null
+++ b/VoxCPM/app.py
@@ -0,0 +1,274 @@
+import os
+import numpy as np
+import torch
+import gradio as gr
+import spaces
+from typing import Optional, Tuple
+from funasr import AutoModel
+from pathlib import Path
+os.environ["TOKENIZERS_PARALLELISM"] = "false"
+if os.environ.get("HF_REPO_ID", "").strip() == "":
+ os.environ["HF_REPO_ID"] = "openbmb/VoxCPM-0.5B"
+
+import voxcpm
+
+
+class VoxCPMDemo:
+ def __init__(self) -> None:
+ self.device = "cuda" if torch.cuda.is_available() else "cpu"
+ print(f"🚀 Running on device: {self.device}")
+
+ # ASR model for prompt text recognition
+ self.asr_model_id = "iic/SenseVoiceSmall"
+ self.asr_model: Optional[AutoModel] = AutoModel(
+ model=self.asr_model_id,
+ disable_update=True,
+ log_level='DEBUG',
+ device="cuda:0" if self.device == "cuda" else "cpu",
+ )
+
+ # TTS model (lazy init)
+ self.voxcpm_model: Optional[voxcpm.VoxCPM] = None
+ self.default_local_model_dir = "./models/VoxCPM-0.5B"
+
+ # ---------- Model helpers ----------
+ def _resolve_model_dir(self) -> str:
+ """
+ Resolve model directory:
+ 1) Use local checkpoint directory if exists
+ 2) If HF_REPO_ID env is set, download into models/{repo}
+ 3) Fallback to 'models'
+ """
+ if os.path.isdir(self.default_local_model_dir):
+ return self.default_local_model_dir
+
+ repo_id = os.environ.get("HF_REPO_ID", "").strip()
+ if len(repo_id) > 0:
+ target_dir = os.path.join("models", repo_id.replace("/", "__"))
+ if not os.path.isdir(target_dir):
+ try:
+ from huggingface_hub import snapshot_download # type: ignore
+ os.makedirs(target_dir, exist_ok=True)
+ print(f"Downloading model from HF repo '{repo_id}' to '{target_dir}' ...")
+ snapshot_download(repo_id=repo_id, local_dir=target_dir, local_dir_use_symlinks=False)
+ except Exception as e:
+ print(f"Warning: HF download failed: {e}. Falling back to 'data'.")
+ return "models"
+ return target_dir
+ return "models"
+
+ def get_or_load_voxcpm(self) -> voxcpm.VoxCPM:
+ if self.voxcpm_model is not None:
+ return self.voxcpm_model
+ print("Model not loaded, initializing...")
+ model_dir = self._resolve_model_dir()
+ print(f"Using model dir: {model_dir}")
+ self.voxcpm_model = voxcpm.VoxCPM(voxcpm_model_path=model_dir)
+ print("Model loaded successfully.")
+ return self.voxcpm_model
+
+ # ---------- Functional endpoints ----------
+ def prompt_wav_recognition(self, prompt_wav: Optional[str]) -> str:
+ if prompt_wav is None:
+ return ""
+ res = self.asr_model.generate(input=prompt_wav, language="auto", use_itn=True)
+ text = res[0]["text"].split('|>')[-1]
+ return text
+
+ def generate_tts_audio(
+ self,
+ text_input: str,
+ prompt_wav_path_input: Optional[str] = None,
+ prompt_text_input: Optional[str] = None,
+ cfg_value_input: float = 2.0,
+ inference_timesteps_input: int = 10,
+ do_normalize: bool = True,
+ denoise: bool = True,
+ ) -> Tuple[int, np.ndarray]:
+ """
+ Generate speech from text using VoxCPM; optional reference audio for voice style guidance.
+ Returns (sample_rate, waveform_numpy)
+ """
+ current_model = self.get_or_load_voxcpm()
+
+ text = (text_input or "").strip()
+ if len(text) == 0:
+ raise ValueError("Please input text to synthesize.")
+
+ prompt_wav_path = prompt_wav_path_input if prompt_wav_path_input else None
+ prompt_text = prompt_text_input if prompt_text_input else None
+
+ print(f"Generating audio for text: '{text[:60]}...'")
+ wav = current_model.generate(
+ text=text,
+ prompt_text=prompt_text,
+ prompt_wav_path=prompt_wav_path,
+ cfg_value=float(cfg_value_input),
+ inference_timesteps=int(inference_timesteps_input),
+ normalize=do_normalize,
+ denoise=denoise,
+ )
+ return (16000, wav)
+
+
+# ---------- UI Builders ----------
+
+def create_demo_interface(demo: VoxCPMDemo):
+ """Build the Gradio UI for VoxCPM demo."""
+ # static assets (logo path)
+ gr.set_static_paths(paths=[Path.cwd().absolute()/"assets"])
+
+ with gr.Blocks(
+ theme=gr.themes.Soft(
+ primary_hue="blue",
+ secondary_hue="gray",
+ neutral_hue="slate",
+ font=[gr.themes.GoogleFont("Inter"), "Arial", "sans-serif"]
+ ),
+ css="""
+ .logo-container {
+ text-align: center;
+ margin: 0.5rem 0 1rem 0;
+ }
+ .logo-container img {
+ height: 80px;
+ width: auto;
+ max-width: 200px;
+ display: inline-block;
+ }
+ /* Bold accordion labels */
+ #acc_quick details > summary,
+ #acc_tips details > summary {
+ font-weight: 600 !important;
+ font-size: 1.1em !important;
+ }
+ /* Bold labels for specific checkboxes */
+ #chk_denoise label,
+ #chk_denoise span,
+ #chk_normalize label,
+ #chk_normalize span {
+ font-weight: 600;
+ }
+ """
+ ) as interface:
+ # Header logo
+ gr.HTML('')
+
+ # Quick Start
+ with gr.Accordion("📋 Quick Start Guide ｜快速入门", open=False, elem_id="acc_quick"):
+ gr.Markdown("""
+ ### How to Use ｜使用说明
+ 1. **(Optional) Provide a Voice Prompt** - Upload or record an audio clip to provide the desired voice characteristics for synthesis.
+ **（可选）提供参考声音** - 上传或录制一段音频，为声音合成提供音色、语调和情感等个性化特征
+ 2. **(Optional) Enter prompt text** - If you provided a voice prompt, enter the corresponding transcript here (auto-recognition available).
+ **（可选项）输入参考文本** - 如果提供了参考语音，请输入其对应的文本内容（支持自动识别）。
+ 3. **Enter target text** - Type the text you want the model to speak.
+ **输入目标文本** - 输入您希望模型朗读的文字内容。
+ 4. **Generate Speech** - Click the "Generate" button to create your audio.
+ **生成语音** - 点击"生成"按钮，即可为您创造出音频。
+ """)
+
+ # Pro Tips
+ with gr.Accordion("💡 Pro Tips ｜使用建议", open=False, elem_id="acc_tips"):
+ gr.Markdown("""
+ ### Prompt Speech Enhancement｜参考语音降噪
+ - **Enable** to remove background noise for a clean, studio-like voice, with an external ZipEnhancer component.
+ **启用**：通过 ZipEnhancer 组件消除背景噪音，获得更好的音质。
+ - **Disable** to preserve the original audio's background atmosphere.
+ **禁用**：保留原始音频的背景环境声，如果想复刻相应声学环境。
+
+ ### Text Normalization｜文本正则化
+ - **Enable** to process general text with an external WeTextProcessing component.
+ **启用**：使用 WeTextProcessing 组件，可处理常见文本。
+ - **Disable** to use VoxCPM's native text understanding ability. For example, it supports phonemes input ({HH AH0 L OW1}), try it!
+ **禁用**：将使用 VoxCPM 内置的文本理解能力。如，支持音素输入（如 {da4}{jia1}好）和公式符号合成，尝试一下！
+
+ ### CFG Value｜CFG 值
+ - **Lower CFG** if the voice prompt sounds strained or expressive.
+ **调低**：如果提示语音听起来不自然或过于夸张。
+ - **Higher CFG** for better adherence to the prompt speech style or input text.
+ **调高**：为更好地贴合提示音频的风格或输入文本。
+
+ ### Inference Timesteps｜推理时间步
+ - **Lower** for faster synthesis speed.
+ **调低**：合成速度更快。
+ - **Higher** for better synthesis quality.
+ **调高**：合成质量更佳。
+ """)
+
+ # Main controls
+ with gr.Row():
+ with gr.Column():
+ prompt_wav = gr.Audio(
+ sources=["upload", 'microphone'],
+ type="filepath",
+ label="Prompt Speech (Optional, or let VoxCPM improvise)",
+ value="./examples/example.wav",
+ )
+ DoDenoisePromptAudio = gr.Checkbox(
+ value=False,
+ label="Prompt Speech Enhancement",
+ elem_id="chk_denoise",
+ info="We use ZipEnhancer model to denoise the prompt audio."
+ )
+ with gr.Row():
+ prompt_text = gr.Textbox(
+ value="Just by listening a few minutes a day, you'll be able to eliminate negative thoughts by conditioning your mind to be more positive.",
+ label="Prompt Text",
+ placeholder="Please enter the prompt text. Automatic recognition is supported, and you can correct the results yourself..."
+ )
+ run_btn = gr.Button("Generate Speech", variant="primary")
+
+ with gr.Column():
+ cfg_value = gr.Slider(
+ minimum=1.0,
+ maximum=3.0,
+ value=2.0,
+ step=0.1,
+ label="CFG Value (Guidance Scale)",
+ info="Higher values increase adherence to prompt, lower values allow more creativity"
+ )
+ inference_timesteps = gr.Slider(
+ minimum=4,
+ maximum=30,
+ value=10,
+ step=1,
+ label="Inference Timesteps",
+ info="Number of inference timesteps for generation (higher values may improve quality but slower)"
+ )
+ with gr.Row():
+ text = gr.Textbox(
+ value="VoxCPM is an innovative end-to-end TTS model from ModelBest, designed to generate highly realistic speech.",
+ label="Target Text",
+ )
+ with gr.Row():
+ DoNormalizeText = gr.Checkbox(
+ value=False,
+ label="Text Normalization",
+ elem_id="chk_normalize",
+ info="We use wetext library to normalize the input text."
+ )
+ audio_output = gr.Audio(label="Output Audio")
+
+ # Wiring
+ run_btn.click(
+ fn=demo.generate_tts_audio,
+ inputs=[text, prompt_wav, prompt_text, cfg_value, inference_timesteps, DoNormalizeText, DoDenoisePromptAudio],
+ outputs=[audio_output],
+ show_progress=True,
+ api_name="generate",
+ )
+ prompt_wav.change(fn=demo.prompt_wav_recognition, inputs=[prompt_wav], outputs=[prompt_text])
+
+ return interface
+
+
+def run_demo(server_name: str = "localhost", server_port: int = 7860, show_error: bool = True):
+ demo = VoxCPMDemo()
+ interface = create_demo_interface(demo)
+ # Recommended to enable queue on Spaces for better throughput
+ interface.queue(max_size=10).launch(server_name=server_name, server_port=server_port, show_error=show_error)
+
+
+if __name__ == "__main__":
+ run_demo()
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+oid sha256:49f6eb7998135ad49f5dd0ee1fa2c099d79a016ab59fe29fc039f7f32ef8f5ca
+size 144982
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+++ b/VoxCPM/ckpts/.gitattributes
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+*.7z filter=lfs diff=lfs merge=lfs -text
+*.arrow filter=lfs diff=lfs merge=lfs -text
+*.bin filter=lfs diff=lfs merge=lfs -text
+*.bz2 filter=lfs diff=lfs merge=lfs -text
+*.ckpt filter=lfs diff=lfs merge=lfs -text
+*.ftz filter=lfs diff=lfs merge=lfs -text
+*.gz filter=lfs diff=lfs merge=lfs -text
+*.h5 filter=lfs diff=lfs merge=lfs -text
+*.joblib filter=lfs diff=lfs merge=lfs -text
+*.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.mlmodel filter=lfs diff=lfs merge=lfs -text
+*.model filter=lfs diff=lfs merge=lfs -text
+*.msgpack filter=lfs diff=lfs merge=lfs -text
+*.npy filter=lfs diff=lfs merge=lfs -text
+*.npz filter=lfs diff=lfs merge=lfs -text
+*.onnx filter=lfs diff=lfs merge=lfs -text
+*.ot filter=lfs diff=lfs merge=lfs -text
+*.parquet filter=lfs diff=lfs merge=lfs -text
+*.pb filter=lfs diff=lfs merge=lfs -text
+*.pickle filter=lfs diff=lfs merge=lfs -text
+*.pkl filter=lfs diff=lfs merge=lfs -text
+*.pt filter=lfs diff=lfs merge=lfs -text
+*.pth filter=lfs diff=lfs merge=lfs -text
+*.rar filter=lfs diff=lfs merge=lfs -text
+*.safetensors filter=lfs diff=lfs merge=lfs -text
+saved_model/**/* filter=lfs diff=lfs merge=lfs -text
+*.tar.* filter=lfs diff=lfs merge=lfs -text
+*.tar filter=lfs diff=lfs merge=lfs -text
+*.tflite filter=lfs diff=lfs merge=lfs -text
+*.tgz filter=lfs diff=lfs merge=lfs -text
+*.wasm filter=lfs diff=lfs merge=lfs -text
+*.xz filter=lfs diff=lfs merge=lfs -text
+*.zip filter=lfs diff=lfs merge=lfs -text
+*.zst filter=lfs diff=lfs merge=lfs -text
+*tfevents* filter=lfs diff=lfs merge=lfs -text
+assets/voxcpm_model.png filter=lfs diff=lfs merge=lfs -text
diff --git a/VoxCPM/ckpts/README.md b/VoxCPM/ckpts/README.md
new file mode 100644
index 0000000000000000000000000000000000000000..e8e96fcff735d12d90d547cd6df81637d13e3039
--- /dev/null
+++ b/VoxCPM/ckpts/README.md
@@ -0,0 +1,238 @@
+---
+license: apache-2.0
+language:
+- en
+- zh
+base_model:
+- openbmb/MiniCPM4-0.5B
+pipeline_tag: text-to-speech
+library_name: voxcpm
+tags:
+- text-to-speech
+- speech
+- speech generation
+- voice cloning
+---
+
+## 🎙️ VoxCPM: Tokenizer-Free TTS for Context-Aware Speech Generation and True-to-Life Voice Cloning
+
+
+[](https://github.com/OpenBMB/VoxCPM/) [](https://huggingface.co/openbmb/VoxCPM-0.5B) [](https://huggingface.co/spaces/OpenBMB/VoxCPM-Demo) [](https://openbmb.github.io/VoxCPM-demopage/)
+
+
+
+
+
+
+
",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ },
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+ "lstrip": false,
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+ "rstrip": false,
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+ },
+ "unk_token": {
+ "content": "",
+ "lstrip": false,
+ "normalized": false,
+ "rstrip": false,
+ "single_word": false
+ }
+}
diff --git a/VoxCPM/ckpts/tokenizer.json b/VoxCPM/ckpts/tokenizer.json
new file mode 100644
index 0000000000000000000000000000000000000000..5405eda8fc32d18fb5a304cb1e292abf6c61dc3f
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+ },
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