0463028bc2
* whisper : check state->ctx_metal not null
* whisper : add whisper_context_params { use_gpu }
* whisper : new API with params & deprecate old API
* examples : use no-gpu param && whisper_init_from_file_with_params
* whisper.objc : enable metal & disable on simulator
* whisper.swiftui, metal : enable metal & support load default.metallib
* whisper.android : use new API
* bindings : use new API
* addon.node : fix build & test
* bindings : updata java binding
* bindings : add missing whisper_context_default_params_by_ref WHISPER_API for java
* metal : use SWIFTPM_MODULE_BUNDLE for GGML_SWIFT and reuse library load
* metal : move bundle var into block
* metal : use SWIFT_PACKAGE instead of GGML_SWIFT
* style : minor updates
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
|
||
|---|---|---|
| .. | ||
| CMakeLists.txt | ||
| README.md | ||
| stream.cpp | ||
stream
This is a naive example of performing real-time inference on audio from your microphone.
The stream tool samples the audio every half a second and runs the transcription continously.
More info is available in issue #10.
./stream -m ./models/ggml-base.en.bin -t 8 --step 500 --length 5000
https://user-images.githubusercontent.com/1991296/194935793-76afede7-cfa8-48d8-a80f-28ba83be7d09.mp4
Sliding window mode with VAD
Setting the --step argument to 0 enables the sliding window mode:
./stream -m ./models/ggml-small.en.bin -t 6 --step 0 --length 30000 -vth 0.6
In this mode, the tool will transcribe only after some speech activity is detected. A very
basic VAD detector is used, but in theory a more sophisticated approach can be added. The
-vth argument determines the VAD threshold - higher values will make it detect silence more often.
It's best to tune it to the specific use case, but a value around 0.6 should be OK in general.
When silence is detected, it will transcribe the last --length milliseconds of audio and output
a transcription block that is suitable for parsing.
Building
The stream tool depends on SDL2 library to capture audio from the microphone. You can build it like this:
# Install SDL2 on Linux
sudo apt-get install libsdl2-dev
# Install SDL2 on Mac OS
brew install sdl2
make stream
Ensure you are at the root of the repo when running make stream. Not within the examples/stream dir
as the libraries needed like common-sdl.h are located within examples. Attempting to compile within
examples/steam means your compiler cannot find them and it gives an error it cannot find the file.
whisper.cpp/examples/stream$ make stream
g++ stream.cpp -o stream
stream.cpp:6:10: fatal error: common/sdl.h: No such file or directory
6 | #include "common/sdl.h"
| ^~~~~~~~~~~~~~
compilation terminated.
make: *** [<builtin>: stream] Error 1
Web version
This tool can also run in the browser: examples/stream.wasm