2022-10-23 08:36:36 +00:00
# whisper.objc
Minimal Obj-C application for automatic offline speech recognition.
The inference runs locally, on-device.
2022-10-23 09:51:09 +00:00
https://user-images.githubusercontent.com/1991296/197385372-962a6dea-bca1-4d50-bf96-1d8c27b98c81.mp4
2022-10-23 08:36:36 +00:00
2022-11-27 08:48:59 +00:00
Real-time transcription demo:
https://user-images.githubusercontent.com/1991296/204126266-ce4177c6-6eca-4bd9-bca8-0e46d9da2364.mp4
2022-10-23 08:36:36 +00:00
## Usage
```java
git clone https://github.com/ggerganov/whisper.cpp
open whisper.cpp/examples/whisper.objc/whisper.objc.xcodeproj/
2023-05-14 06:47:02 +00:00
// If you don't want to convert a Core ML model, you can skip this step by create dummy model
mkdir models/ggml-base.en-encoder.mlmodelc
2022-10-23 08:36:36 +00:00
```
Make sure to build the project in `Release` :
< img width = "947" alt = "image" src = "https://user-images.githubusercontent.com/1991296/197382607-9e1e6d1b-79fa-496f-9d16-b71dc1535701.png" >
2022-12-19 20:09:21 +00:00
2023-05-14 06:47:02 +00:00
Also, don't forget to add the `-DGGML_USE_ACCELERATE` compiler flag for `ggml.c` in Build Phases.
2022-12-19 20:09:21 +00:00
This can significantly improve the performance of the transcription:
< img width = "1072" alt = "image" src = "https://user-images.githubusercontent.com/1991296/208511239-8d7cdbd1-aa48-41b5-becd-ca288d53cc07.png" >
2023-03-22 20:16:04 +00:00
2023-05-14 06:47:02 +00:00
If you want to enable Core ML support, you can add the `-DWHISPER_USE_COREML -DWHISPER_COREML_ALLOW_FALLBACK` compiler flag for `whisper.cpp` in Build Phases:
< img width = "1072" alt = "image" src = "https://github.com/ggerganov/whisper.cpp/assets/3001525/103e8f57-6eb6-490d-a60c-f6cf6c319324" >
Then follow the [`Core ML support` section of readme ](../../README.md#core-ml-support ) for convert the model.
2023-03-22 20:16:04 +00:00
In this project, it also added `-O3 -DNDEBUG` to `Other C Flags` , but adding flags to app proj is not ideal in real world (applies to all C/C++ files), consider splitting xcodeproj in workspace in your own project.