A user on the LocalLLaMA forum raised an interesting question: is it possible to create a speech-to-speech model small enough to run directly on a device, without relying on cloud resources?

The challenge of on-device inference

The question highlights one of the main challenges in developing artificial intelligence applications: balancing model complexity with the hardware capabilities of the device on which it must run. Speech-to-speech models, which convert a voice input into another voice output (possibly in another language), tend to be computationally intensive.

Possible solutions

The user wonders if, in the absence of ready-to-use solutions, it is possible to develop an ad hoc model, optimized for a specific use case. This approach could reduce the model size and computing requirements, making it suitable for execution on resource-constrained devices.