mirror of
https://github.com/ggerganov/whisper.cpp.git
synced 2024-12-28 16:28:50 +00:00
75 lines
3.3 KiB
Markdown
75 lines
3.3 KiB
Markdown
# talk.wasm
|
|
|
|
Talk with an Artificial Intelligence in your browser:
|
|
|
|
[https://user-images.githubusercontent.com/1991296/203411580-fedb4839-05e4-4474-8364-aaf1e9a9b615.mp4](https://user-images.githubusercontent.com/1991296/203845553-f7b44e13-9a15-4fc8-b518-ae8f4c6770fe.mp4)
|
|
|
|
Online demo: https://whisper.ggerganov.com/talk/
|
|
|
|
Terminal version: [examples/talk](/examples/talk)
|
|
|
|
## How it works?
|
|
|
|
This demo leverages 2 modern neural network models to create a high-quality voice chat directly in your browser:
|
|
|
|
- [OpenAI's Whisper](https://github.com/openai/whisper) speech recognition model is used to process your voice and understand what you are saying
|
|
- Upon receiving some voice input, the AI generates a text response using [OpenAI's GPT-2](https://github.com/openai/gpt-2) language model
|
|
- The AI then vocalizes the response using the browser's [Web Speech API](https://developer.mozilla.org/en-US/docs/Web/API/Web_Speech_API)
|
|
|
|
The web page does the processing locally on your machine. The processing of these heavy neural network models in the
|
|
browser is possible by implementing them efficiently in C/C++ and using the browser's WebAssembly SIMD capabilities for
|
|
extra performance:
|
|
|
|
- The Whisper C++ implementation is here: [whisper.h](/whisper.h) / [whisper.cpp](/whisper.cpp)
|
|
- The GPT-2 C++ implementation is here: [gpt-2.h](gpt-2.h) / [gpt-2.cpp](gpt-2.cpp)
|
|
- Both models use a custom tensor library implemented in C: [ggml.h](/ggml.h) / [ggml.c](/ggml.c)
|
|
- The HTML/JS layer is here: [index-tmpl.html](index-tmpl.html)
|
|
- The Emscripten bridge between C/C++ and JS is here: [emscripten.cpp](emscripten.cpp)
|
|
|
|
In order to run the models, the web page first needs to download the model data which is about ~350 MB. The model data
|
|
is then cached in your browser's cache and can be reused in future visits without downloading it again.
|
|
|
|
## Requirements
|
|
|
|
In order to run this demo efficiently, you need to have the following:
|
|
|
|
- Latest Chrome or Firefox browser (Safari is not supported)
|
|
- Run this on a desktop or laptop with modern CPU (a mobile phone will likely not be good enough)
|
|
- Speak phrases that are no longer than 10 seconds - this is the audio context of the AI
|
|
- The web-page uses about 1.8GB of RAM
|
|
|
|
Notice that this demo is using the smallest GPT-2 model, so the generated text responses are not always very good.
|
|
Also, the prompting strategy can likely be improved to achieve better results.
|
|
|
|
The demo is quite computationally heavy, so you need a fast CPU. It's not usual to run these transformer models in a
|
|
browser. Typically, they run on powerful GPUs.
|
|
|
|
Currently, mobile browsers do not support the Fixed-width SIMD WebAssembly capability, so you cannot run this demo
|
|
on a phone or a tablet. Hopefully, in the near future this will become supported.
|
|
|
|
## Todo
|
|
|
|
- Better UI (contributions are welcome)
|
|
- Better GPT-2 prompting
|
|
|
|
## Build instructions
|
|
|
|
```bash
|
|
# build using Emscripten (v3.1.2)
|
|
git clone https://github.com/ggerganov/whisper.cpp
|
|
cd whisper.cpp
|
|
mkdir build-em && cd build-em
|
|
emcmake cmake ..
|
|
make -j
|
|
|
|
# copy the produced page to your HTTP path
|
|
cp bin/talk.wasm/* /path/to/html/
|
|
cp bin/libtalk.worker.js /path/to/html/
|
|
```
|
|
|
|
## Feedback
|
|
|
|
If you have any comments or ideas for improvement, please drop a comment in the following discussion:
|
|
|
|
https://github.com/ggerganov/whisper.cpp/discussions/167
|