Create README.md

Makefile

@@ -19,7 +19,7 @@ run: main
 .PHONY: samples
 samples:
 	@echo "Downloading samples..."
-	mkdir -p samples
+	@mkdir -p samples
 	@wget --quiet --show-progress -O samples/gb0.ogg https://upload.wikimedia.org/wikipedia/commons/2/22/George_W._Bush%27s_weekly_radio_address_%28November_1%2C_2008%29.oga
 	@wget --quiet --show-progress -O samples/gb1.ogg https://upload.wikimedia.org/wikipedia/commons/1/1f/George_W_Bush_Columbia_FINAL.ogg
 	@wget --quiet --show-progress -O samples/hp0.ogg https://upload.wikimedia.org/wikipedia/en/d/d4/En.henryfphillips.ogg
@@ -31,10 +31,11 @@ samples:
 .PHONY: tiny.en
 tiny.en: main
 	@echo "Downloading tiny.en (75 MB just once)"
-	mkdir -p models
+	@mkdir -p models
 	@if [ ! -f models/ggml-tiny.en.bin ]; then \
 		wget --quiet --show-progress -O models/ggml-tiny.en.bin https://ggml.ggerganov.com/ggml-model-whisper-tiny.en.bin ; \
 	fi
+	@echo ""
 	@echo "==============================================="
 	@echo "Running tiny.en on all samples in ./samples ..."
 	@echo "==============================================="
@@ -51,10 +52,11 @@ tiny.en: main
 .PHONY: base.en
 base.en: main
 	@echo "Downloading base.en (142 MB just once)"
-	mkdir -p models
+	@mkdir -p models
 	@if [ ! -f models/ggml-base.en.bin ]; then \
 		wget --quiet --show-progress -O models/ggml-base.en.bin https://ggml.ggerganov.com/ggml-model-whisper-base.en.bin ; \
 	fi
+	@echo ""
 	@echo "==============================================="
 	@echo "Running base.en on all samples in ./samples ..."
 	@echo "==============================================="
@@ -71,10 +73,11 @@ base.en: main
 .PHONY: small.en
 small.en: main
 	@echo "Downloading small.en (466 MB just once)"
-	mkdir -p models
+	@mkdir -p models
 	@if [ ! -f models/ggml-small.en.bin ]; then \
 		wget --quiet --show-progress -O models/ggml-small.en.bin https://ggml.ggerganov.com/ggml-model-whisper-small.en.bin ; \
 	fi
+	@echo ""
 	@echo "==============================================="
 	@echo "Running small.en on all samples in ./samples ..."
 	@echo "==============================================="
@@ -91,10 +94,11 @@ small.en: main
 .PHONY: medium.en
 medium.en: main
 	@echo "Downloading medium.en (1.5 GB just once)"
-	mkdir -p models
+	@mkdir -p models
 	@if [ ! -f models/ggml-medium.en.bin ]; then \
 		wget --quiet --show-progress -O models/ggml-medium.en.bin https://ggml.ggerganov.com/ggml-model-whisper-medium.en.bin ; \
 	fi
+	@echo ""
 	@echo "==============================================="
 	@echo "Running medium.en on all samples in ./samples ..."
 	@echo "==============================================="

README.md

@@ -0,0 +1,116 @@
+# whisper.cpp
+
+C/C++ port of [OpenAI's Whisper](https://github.com/openai/whisper) speech-to-text model
+
+- Plain C/C++ implementation without dependencies
+- ARM_NEON and AVX intrinsics support
+- F16 support
+
+## Usage
+
+For a quick demo, simply run `make base.en`:
+
+```bash
+$ make base.en
+
+Downloading base.en (142 MB just once)
+mkdir -p models
+models/ggml-base.en.bin      100%[=================================>] 141.11M  7.50MB/s    in 19s
+
+===============================================
+Running base.en on all samples in ./samples ...
+===============================================
+
+----------------------------------------------
+[+] Running base.en on samples/jfk.wav ... (run 'ffplay samples/jfk.wav' to listen)
+----------------------------------------------
+
+whisper_model_load: loading model from 'models/ggml-base.en.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: mem_required  = 782.00 MB
+whisper_model_load: adding 1607 extra tokens
+whisper_model_load: ggml ctx size = 186.26 MB
+whisper_model_load: memory size =    45.66 MB
+whisper_model_load: model size  =   140.54 MB
+log_mel_spectrogram: n_sample = 176000, n_len = 1100
+log_mel_spectrogram: recording length: 11.000000 s
+
+ And so my fellow Americans ask not what your country can do for you. Ask what you can do for your country.
+
+main:     load time =    60.62 ms
+main:      mel time =    38.69 ms
+main:   sample time =     2.36 ms
+main:   encode time =   875.63 ms / 145.94 ms per layer
+main:   decode time =   103.17 ms
+main:    total time =  1081.13 ms
+
+```
+
+The command downloads the `base.en` model converted to custom `ggml` format and runs the inference on all `.wav` samples in the folder `samples`.
+
+If you want some extra audio samples to play with, simply run:
+
+```
+make samples
+```
+
+This will download a few more audio files from Wikipedia and convert them to 16-bit WAV format via `ffmpeg`.
+
+You can download and run the other `.en` models as follows:
+
+```
+make tiny.en
+make base.en
+make small.en
+make medium.en
+```
+
+For detailed usage instructions, run: `./main -h`
+
+Note that `whisper.cpp` runs only with 16-bit WAV files, so make sure to convert your input before running the tool.
+For example, you can use `ffmpeg` like this:
+
+```bash
+ffmpeg -i input.mp3 -ar 16000 -ac 1 -c:a pcm_s16le output.wav
+```
+
+## Limitations
+
+- Only `.en` models are supported
+- Very basic greedy sampling scheme - always pick up the top token
+- No timestamps
+- English only
+- Inference only
+- Runs on the CPU
+- Only mono-channel 16-bit WAV is supported
+
+## Memory usage
+
+| Model | Mem |
+| ---   | --- |
+| tiny.en | ~600 MB |
+| base.en | ~800 MB |
+| small.en | ~1.6 GB |
+| medium.en | ~3.5 GB |
+
+## ggml format
+
+The original models are converted to a custom binary format. This allows to pack everything needed into a single file:
+
+- model parameters
+- mel filters
+- vocabulary
+- weights
+
+For more details, see the conversion script [convert-pt-to-ggml.py](convert-pt-to-ggml.py)