Evaluating real-time speech inference
Published on September 18, 2024, the article presents Moshi, a 7.6-billion-parameter speech-to-speech model, and Mimi, a streaming audio codec.
Source: Moshi: um modelo open source de speech-to-speech (x.com). Text prepared with AI from this source.
What happened and what to do
The September 18, 2024 article presents Moshi, an open-source speech-to-speech model with 7.6 billion parameters, accompanied by Mimi, a streaming audio codec. The publication says the release includes checkpoints and inference code for Candle, PyTorch, and MLX, enabling evaluation across different frameworks and hardware.
A company exploring voice interfaces could build a proof of concept to test latency, audio quality, hardware compatibility, and integration with internal systems. The work could include a technical evaluation, an API for the application, and performance and cost monitoring, without assuming that adopting this particular model is the right solution.
How the consultancy can help
Wendelmaques can diagnose voice and infrastructure requirements, define a proof of concept with evaluation criteria, and implement the required inference, integration, and monitoring. The scope can also include operating the solution.
Next step
Send a short description of your voice use case and available infrastructure to receive a scoped proposal.
Let's assess your project
I reply with scope and a proposal.