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83c742f1a7
Using a Phase Vocoder for speeding up the audio tempo by scaling down the frequencies in the frequency domain. This reduces the computation in the Encoder by a factor of 2. The transcription accuracy is degraded, but for slow to normal speech - it seems to be still very good. I think this can find application for real-time transcription - i.e. the "stream" example. |
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.. | ||
CMakeLists.txt | ||
main.cpp | ||
README.md |
main
This is the main example demonstrating most of the functionality of the Whisper model.
It can be used as a reference for using the whisper.cpp
library in other projects.
./main -h
usage: ./bin/main [options] file0.wav file1.wav ...
-h, --help show this help message and exit
-s SEED, --seed SEED RNG seed (default: -1)
-t N, --threads N number of threads to use during computation (default: 4)
-p N, --processors N number of processors to use during computation (default: 1)
-ot N, --offset-t N time offset in milliseconds (default: 0)
-on N, --offset-n N segment index offset (default: 0)
-mc N, --max-context N maximum number of text context tokens to store (default: max)
-ml N, --max-len N maximum segment length in characters (default: 0)
-wt N, --word-thold N word timestamp probability threshold (default: 0.010000)
-v, --verbose verbose output
--translate translate from source language to english
-otxt, --output-txt output result in a text file
-ovtt, --output-vtt output result in a vtt file
-osrt, --output-srt output result in a srt file
-owts, --output-words output script for generating karaoke video
-ps, --print_special print special tokens
-pc, --print_colors print colors
-nt, --no_timestamps do not print timestamps
-l LANG, --language LANG spoken language (default: en)
-m FNAME, --model FNAME model path (default: models/ggml-base.en.bin)
-f FNAME, --file FNAME input WAV file path
-h, --help show this help message and exit