Crates.io | rusty-whisper |
lib.rs | rusty-whisper |
version | 0.1.3 |
source | src |
created_at | 2023-11-24 18:17:43.076677 |
updated_at | 2023-12-05 18:26:40.467275 |
description | Rust implementation of Whisper |
homepage | |
repository | https://github.com/igor-yusupov/rusty-whisper/ |
max_upload_size | |
id | 1047263 |
size | 58,871 |
Rust implementation of Whisper. More information about model: https://github.com/openai/whisper
This crate is based on tract.
Download weights and example audio file and run simple inference code:
use rusty_whisper::Whisper;
fn main() {
let whisper = Whisper::new(
"weights/encoder.onnx",
"weights/decoder.onnx",
"weights/multilingual.tiktoken",
"weights/positional_embedding.npz",
"weights/mel_filters.npz",
);
let result = whisper.recognize_from_audio("data/audio.wav");
println!("{}", result);
}
The model works 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:
ffmpeg -i input.mp3 -ar 16000 -ac 1 -c:a pcm_s16le output.wav