

GLM 4 Voice
Overview :
GLM-4-Voice is an end-to-end voice model developed by a team from Tsinghua University, capable of directly understanding and generating Chinese and English speech for real-time dialogue. Leveraging advanced speech recognition and synthesis technologies, it achieves seamless conversion from speech to text and back to speech, boasting low latency and high conversational intelligence. The model is optimized for intellectual engagement and expressive synthesis capabilities in the voice modality, making it suitable for scenarios requiring real-time voice interaction.
Target Users :
The target audience for GLM-4-Voice includes developers, enterprises, and anyone needing real-time voice interaction. For developers, it provides a powerful tool for building voice interaction applications; for businesses, it enhances the efficiency and quality of customer service; for individual users, it offers an innovative voice interaction experience.
Use Cases
? Guiding users to relax with a soothing voice.
? Commenting on a football match with an excited voice.
? Telling a ghost story in a sorrowful tone.
Features
? Speech Recognition: Converts continuous voice input into discrete tokens.
? Speech Synthesis: Transforms discrete speech tokens into continuous voice output.
? Emotion Control: Modifies the voice's emotion, tone, speed, and dialect based on user commands.
? Streaming Inference: Supports the simultaneous output of both text and speech modalities, reducing end-to-end dialogue latency.
? Pre-training Capacity: Trained on millions of hours of audio and trillions of token audio-text paired data, possessing powerful audio comprehension and modeling abilities.
? Multilingual Support: Directly understands and generates speech in both Chinese and English for real-time dialogue.
How to Use
1. First, download the repository: Use Git commands to clone the project to your local machine.
2. Install dependencies: Follow the instructions in the requirements.txt file to install the necessary Python dependencies.
3. Download models: Refer to the project guidelines to download the required voice models and tokenizers.
4. Start the model service: Run the model_server.py script to initiate the model service.
5. Launch the Web Demo: Execute the web_demo.py script to start the Web Demo service.
6. Access the Web Demo: Open your browser and go to http://127.0.0.1:8888 to use the Web Demo.
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