Local Low Latency Speech-to-Speech with Mistral 7B

In this video, the creator from All About AI demonstrates a local low latency speech-to-speech system using Mistral 7B, OpenVoice, and Whisper. The system is fully offline, open-source, and does not rely on APIs, ensuring low latency. The video begins with an introduction to the system and its components, followed by a simplified flowchart explaining the process. The setup involves using LM Studio to run the Mistral 7B model, OpenVoice for text-to-speech, and Whisper for speech-to-text. The Python code is reviewed, highlighting key functions such as audio playback, model loading, transcription, and the chatbot conversation loop. Two tests are conducted to showcase the system’s performance and latency. The first test involves a conversation with a female hacker persona named Julie, while the second test features a conversation with a crazy AI researcher persona named Johnny. The video also demonstrates a simulation of two chatbots conversing with each other. The creator emphasizes the potential for further optimization and the benefits of running the system offline. The video concludes with an invitation to join the membership for access to the code and further discussions.