Robust Speech-to-Text, Running Locally On Quest VR Headset

August 16, 2024 by Donald Papp 3 Comments

[saurabhchalke] recently released whisper.unity, a Unity package that implements whisper locally on the Meta Quest 3 VR headset, bringing nearly real-time transcription of natural speech to the device in an easy-to-use way.

Whisper is a robust and free open source neural network capable of quickly recognizing and transcribing multilingual natural speech with nearly-human level accuracy, and this package implements it entirely on-device, meaning it runs locally and doesn’t interact with any remote service.

It used to be that voice input for projects was a tricky business with iffy results and a strong reliance on speaker training and wake-words, but that’s no longer the case. Reliable and nearly real-time speech recognition is something that’s easily within the average hacker’s reach nowadays.

We covered Whisper getting a plain C/C++ implementation which opened the door to running on a variety of platforms and devices. [Macoron] turned whisper.cpp into a Unity binding which served as inspiration for this project, in which [saurabhchalke] turned it into a Quest 3 package. So if you are doing any VR projects in Unity and want reliable speech input with a side order of easy translation, it’s never been simpler.

Here’s A Plain C/C++ Implementation Of AI Speech Recognition, So Get Hackin’

November 27, 2022 by Donald Papp 19 Comments

[Georgi Gerganov] recently shared a great resource for running high-quality AI-driven speech recognition in a plain C/C++ implementation on a variety of platforms. The automatic speech recognition (ASR) model is fully implemented using only two source files and requires no dependencies. As a result, the high-quality speech recognition doesn’t involve calling remote APIs, and can run locally on different devices in a fairly straightforward manner. The image above shows it running locally on an iPhone 13, but it can do more than that.

Implementing a robust speech transcription that runs locally on a variety of devices is much easier with [Georgi]’s port of OpenAI’s *Whisper*.

[Georgi]’s work is a port of OpenAI’s Whisper model, a remarkably-robust piece of software that does a truly impressive job of turning human speech into text. Whisper is easy to set up and play with, but this port makes it easier to get the system working in other ways. Having such a lightweight implementation of the model means it can be more easily integrated over a variety of different platforms and projects.

The usual way that OpenAI’s Whisper works is to feed it an audio file, and it spits out a transcription. But [Georgi] shows off something else that might start giving hackers ideas: a simple real-time audio input example.

By using a tool to stream audio and feed it to the system every half-second, one can obtain pretty good (sort of) real-time results! This of course isn’t an ideal method, but the robustness and accuracy of Whisper is such that the results look pretty great nevertheless.

You can watch a quick demo of that in the video just under the page break. If it gives you some ideas, head over to the project’s GitHub repository and get hackin’!

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