mirror of https://github.com/ggml-org/whisper.cpp.git synced 2026-09-21 13:37:35 -05:00

Files

T

Daniel Bevenius 339f2b4e27 bindings-javascript : remove package.json from git (#4001 )

This commit removes package.json from git and adds package.json to the
gitignore.

This file is generated by CMake configure and will be updated and
overwritten causing a lot of noise in the git history.
It have also been updated manually as part of our release process which
will not be needed either.

2026-08-20 15:59:54 +02:00

.gitignore

bindings-javascript : remove package.json from git (#4001 )

2026-08-20 15:59:54 +02:00

CMakeLists.txt

Node.js package (#260 )

2022-12-12 20:17:27 +02:00

emscripten.cpp

whisper : add context param to disable gpu (#1293 )

2023-11-06 11:04:24 +02:00

libwhisper.worker.js

ggml : sync (ggml-alloc, GPU, eps, etc.) (#1220 )

2023-09-05 13:54:40 +03:00

package-tmpl.json

cmake : update semver and release process [no ci] (#3996 )

2026-08-20 09:34:27 +02:00

README.md

bindings.javascript : update test instructions [no ci] (#2951 )

2025-03-26 14:49:12 +01:00

whisper.js

wchess : whisper assisted chess (#1595 )

2023-12-14 15:58:26 +02:00

README.md

whisper.cpp

Node.js package for Whisper speech recognition

Package: https://www.npmjs.com/package/whisper.cpp

Details

The performance is comparable to when running whisper.cpp in the browser via WASM.

The API is currently very rudimentary: bindings/javascript/emscripten.cpp

For sample usage check tests/test-whisper.js

Package building + test

# load emscripten
source /path/to/emsdk/emsdk_env.sh

# clone repo
git clone https://github.com/ggerganov/whisper.cpp
cd whisper.cpp

# grab base.en model
./models/download-ggml-model.sh base.en

# prepare PCM sample for testing
ffmpeg -i samples/jfk.wav -f f32le -acodec pcm_f32le samples/jfk.pcmf32

# build
mkdir build-em && cd build-em
emcmake cmake .. && make -j

# run test
node ../tests/test-whisper.js

# For Node.js versions prior to v16.4.0, experimental features need to be enabled:
node --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js

# publish npm package
make publish-npm

Sample run

$ node --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js

whisper_model_load: loading model from 'whisper.bin'
whisper_model_load: n_vocab       = 51864
whisper_model_load: n_audio_ctx   = 1500
whisper_model_load: n_audio_state = 512
whisper_model_load: n_audio_head  = 8
whisper_model_load: n_audio_layer = 6
whisper_model_load: n_text_ctx    = 448
whisper_model_load: n_text_state  = 512
whisper_model_load: n_text_head   = 8
whisper_model_load: n_text_layer  = 6
whisper_model_load: n_mels        = 80
whisper_model_load: f16           = 1
whisper_model_load: type          = 2
whisper_model_load: adding 1607 extra tokens
whisper_model_load: mem_required  =  506.00 MB
whisper_model_load: ggml ctx size =  140.60 MB
whisper_model_load: memory size   =   22.83 MB
whisper_model_load: model size    =  140.54 MB

system_info: n_threads = 8 / 10 | AVX = 0 | AVX2 = 0 | AVX512 = 0 | NEON = 0 | F16C = 0 | FP16_VA = 0 | WASM_SIMD = 1 | BLAS = 0 |

operator(): processing 176000 samples, 11.0 sec, 8 threads, 1 processors, lang = en, task = transcribe ...

[00:00:00.000 --> 00:00:11.000]   And so my fellow Americans, ask not what your country can do for you, ask what you can do for your country.

whisper_print_timings:     load time =   162.37 ms
whisper_print_timings:      mel time =   183.70 ms
whisper_print_timings:   sample time =     4.27 ms
whisper_print_timings:   encode time =  8582.63 ms / 1430.44 ms per layer
whisper_print_timings:   decode time =   436.16 ms / 72.69 ms per layer
whisper_print_timings:    total time =  9370.90 ms