Node.js package for Whisper speech recognition
-For sample usage check [tests/test-whisper.js](/tests/test-whisper.js)
+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:
+
+https://github.com/ggerganov/whisper.cpp/blob/npm/bindings/javascript/emscripten.cpp
+
+I am hoping that there will be interest in contributions and making it better based on what is needed in practice.
+For sample usage check [tests/test-whisper.js](https://github.com/ggerganov/whisper.cpp/blob/npm/tests/test-whisper.js)
+
+## Package building + test
+
+```bash
+# 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 --experimental-wasm-threads --experimental-wasm-simd ../tests/test-whisper.js
+
+# publish npm package
+make publish-npm
+```
+
+## Sample run
+
+```java
+$ 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
+```