wehub-resource-sync
85 lines
2.5 KiB
JavaScript
85 lines
2.5 KiB
JavaScript
var vosk = require('..')
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const fs = require("fs");
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const { spawn } = require("child_process");
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const { stringifySync } = require('subtitle')
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MODEL_PATH = "model"
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FILE_NAME = "test.wav"
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SAMPLE_RATE = 16000
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BUFFER_SIZE = 4000
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if (!fs.existsSync(MODEL_PATH)) {
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console.log("Please download the model from https://alphacephei.com/vosk/models and unpack as " + MODEL_PATH + " in the current folder.")
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process.exit()
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}
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if (process.argv.length > 2)
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FILE_NAME = process.argv[2]
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vosk.setLogLevel(-1);
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const model = new vosk.Model(MODEL_PATH);
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const rec = new vosk.Recognizer({model: model, sampleRate: SAMPLE_RATE});
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rec.setWords(true);
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const ffmpeg_run = spawn('ffmpeg', ['-loglevel', 'quiet', '-i', FILE_NAME,
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'-ar', String(SAMPLE_RATE) , '-ac', '1',
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'-f', 's16le', '-bufsize', String(BUFFER_SIZE), '-']);
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WORDS_PER_LINE = 7
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const subs = []
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const results = []
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ffmpeg_run.stdout.on('data', (stdout) => {
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if (rec.acceptWaveform(stdout))
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results.push(rec.result());
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results.push(rec.finalResult());
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});
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ffmpeg_run.on('exit', code => {
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rec.free();
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model.free();
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results.forEach(element =>{
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if (!element.hasOwnProperty('result'))
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return;
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const words = element.result;
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if (words.length == 1) {
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subs.push({
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type: 'cue',
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data: {
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start: words[0].start * 1000,
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end: words[0].end * 1000,
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text: words[0].word
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}
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});
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return;
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}
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var start_index = 0;
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var text = words[0].word + " ";
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for (let i = 1; i < words.length; i++) {
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text += words[i].word + " ";
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if (i % WORDS_PER_LINE == 0) {
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subs.push({
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type: 'cue',
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data: {
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start: words[start_index].start * 1000,
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end: words[i].end * 1000,
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text: text.slice(0, text.length-1)
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}
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});
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start_index = i;
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text = "";
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}
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}
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if (start_index != words.length - 1)
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subs.push({
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type: 'cue',
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data: {
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start: words[start_index].start * 1000,
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end: words[words.length-1].end * 1000,
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text: text
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}
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});
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});
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console.log(stringifySync(subs, {format: "SRT"}));
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});
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