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+# MiniMax-Speech Technical Implementation
+
+An unofficial implementation based on the MiniMax-Speech technical report, with core components adapted from [CosyVoice2](https://github.com/FunAudioLLM/CosyVoice).
+
+![MiniMax-Speech Architecture](assets/image.png)
+
+## Overview
+
+This repository provides an implementation of the MiniMax-Speech model, featuring a two-stage training approach for high-quality 24kHz audio generation.
+
+## Key Features
+
+- **24kHz Audio Support**: High-quality audio generation at 24kHz sampling rate
+- **Two-Stage Architecture**: Optimized training pipeline with discrete and continuous representations
+- **Modular Design**: Separate components for audio codec and variational autoencoder
+- **CosyVoice2 Integration**: Leverages proven components from the CosyVoice2 framework
+
+## Architecture
+
+### Stage 1: Audio to Discrete Tokens
+Converts raw audio into discrete representations using the DAC (Descript Audio Codec) framework.
+
+### Stage 2: Discrete Tokens to Continuous Latent Space
+Maps discrete tokens to a continuous latent space using a Variational Autoencoder (VAE).
+
+> **Note**: This implementation uses standard DAC-VAE instead of Flow-VAE.
+
+## Implementation Pipeline
+
+### 1. Model Training
+
+#### DAC Codec
+- Based on the [Descript Audio Codec](https://github.com/descriptinc/descript-audio-codec)
+- Provides efficient audio tokenization
+- Utilizes CosyVoice2's optimized training pipeline
+
+#### DAC-VAE
+- Train using `train_dac_vae.py`
+- Learns continuous latent representations from discrete tokens
+- Architecture adapted from CosyVoice2's VAE implementation
+
+### 2. Feature Extraction
+
+Before training the main model:
+1. Extract discrete tokens using the trained DAC codec
+2. Generate continuous latent representations using the trained DAC-VAE
+
+### 3. Two-Stage Training
+
+Train the models sequentially:
+- **Stage 1**: Audio → Discrete token modeling
+- **Stage 2**: Discrete token → Continuous latent space modeling
+
+## Getting Started
+
+### Prerequisites
+```bash
+# List your dependencies here
+pip install -r requirements.txt
+```
+
+### Training Pipeline
+
+1. **Train DAC Codec** (if not using pretrained)
+   ```bash
+   # Add training command
+   ```
+
+2. **Train DAC-VAE**
+   ```bash
+   python train_dac_vae.py --config configs/dac_vae.yaml
+   ```
+
+3. **Extract Features**
+   ```bash
+   # Add feature extraction commands
+   ```
+
+4. **Train MiniMax-Speech**
+   ```bash
+   # Add main training command
+   ```
+
+## Project Structure
+```
+minimax-speech/
+├── assets/
+│   └── image.png
+├── configs/
+│   └── dac_vae.yaml
+├── models/
+│   ├── dac_codec/
+│   └── dac_vae/
+├── cosyvoice/          # Components from CosyVoice2
+│   ├── flow/
+│   ├── transformer/
+│   └── utils/
+├── train_dac_vae.py
+└── README.md
+```
+
+## Related Projects
+
+This implementation builds upon several key projects:
+
+- **[CosyVoice2](https://github.com/FunAudioLLM/CosyVoice)**: Core model architectures and training pipelines
+- **[Descript Audio Codec](https://github.com/descriptinc/descript-audio-codec)**: Audio tokenization framework
+- **MiniMax-Speech**: Original technical report and methodology
+
+## Citation
+
+If you use this code in your research, please cite:
+
+```bibtex
+@article{minimax-speech,
+  title={MiniMax-Speech},
+  author={[MiniMax team]},
+  year={[2025]}
+  url={https://arxiv.org/pdf/2505.07916}
+}
+
+@misc{cosyvoice2,
+  title={CosyVoice: A Scalable Multilingual Zero-shot Text-to-speech Synthesizer based on Supervised Semantic Tokens},
+  author={[FunAudioLLM Team, SpeechLab@Tongyi, Alibaba Group]},
+  year={2024},
+  url={https://github.com/FunAudioLLM/CosyVoice}
+}
+```
+
+## License
+
+This project follows the licensing terms of its dependencies:
+- CosyVoice2 components: [Check CosyVoice2 License](https://github.com/FunAudioLLM/CosyVoice/blob/main/LICENSE)
+- DAC components: [Apache 2.0 License](https://github.com/descriptinc/descript-audio-codec/blob/main/LICENSE)
+- Original contributions: [Specify your license here]
+
+## Acknowledgments
+
+- **[CosyVoice2](https://github.com/FunAudioLLM/CosyVoice)**: This implementation extensively uses code and architectures from CosyVoice2
+- **[Descript Audio Codec](https://github.com/descriptinc/descript-audio-codec)**: For the DAC implementation
+- **MiniMax team**: For the technical report and methodology
+- **FunAudioLLM team**: For the excellent CosyVoice2 codebase
+
+## Contributing
+
+Contributions are welcome! Please feel free to submit a Pull Request.
+
+## Contact
+
+[Your contact information or links to issues/discussions]