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LLM ASR
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This commit is contained in:
Zakary Timson
2026-02-22 09:29:31 -05:00
parent ca66e8e304
commit abd290246c
4 changed files with 143 additions and 95 deletions
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2
package.json
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@@ -1,6 +1,6 @@
{
"name": "@ztimson/ai-utils",
"version": "0.8.0",
"version": "0.8.1",
"description": "AI Utility library",
"author": "Zak Timson",
"license": "MIT",

209
src/audio.ts
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@@ -35,6 +35,121 @@ print(json.dumps(segments))
`;
}
private async addPunctuation(timestampData: any, llm?: boolean, cadence = 150): Promise<string> {
const countSyllables = (word: string): number => {
word = word.toLowerCase().replace(/[^a-z]/g, '');
if(word.length <= 3) return 1;
const matches = word.match(/[aeiouy]+/g);
let count = matches ? matches.length : 1;
if(word.endsWith('e')) count--;
return Math.max(1, count);
};
let result = '';
timestampData.transcription.filter((word, i) => {
let skip = false;
const prevWord = timestampData.transcription[i - 1];
const nextWord = timestampData.transcription[i + 1];
if(!word.text && nextWord) {
nextWord.offsets.from = word.offsets.from;
nextWord.timestamps.from = word.offsets.from;
} else if(word.text && word.text[0] != ' ' && prevWord) {
prevWord.offsets.to = word.offsets.to;
prevWord.timestamps.to = word.timestamps.to;
prevWord.text += word.text;
skip = true;
}
return !!word.text && !skip;
}).forEach((word: any) => {
const capital = /^[A-Z]/.test(word.text.trim());
const length = word.offsets.to - word.offsets.from;
const syllables = countSyllables(word.text.trim());
const expected = syllables * cadence;
if(capital && length > expected * 2 && word.text[0] == ' ') result += '.';
result += word.text;
});
if(!llm) return result.trim();
return this.ai.language.ask(result, {
system: 'Remove any misplaced punctuation from the following ASR transcript using the replace tool. Avoid modifying words unless there is an obvious typo',
temperature: 0.1,
tools: [{
name: 'replace',
description: 'Use find and replace to fix errors',
args: {
find: {type: 'string', description: 'Text to find', required: true},
replace: {type: 'string', description: 'Text to replace', required: true}
},
fn: (args) => result = result.replace(args.find, args.replace)
}]
}).then(() => result);
}
private async diarizeTranscript(timestampData: any, speakers: any[], llm: boolean): Promise<string> {
const speakerMap = new Map();
let speakerCount = 0;
speakers.forEach((seg: any) => {
if(!speakerMap.has(seg.speaker)) speakerMap.set(seg.speaker, ++speakerCount);
});
const punctuatedText = await this.addPunctuation(timestampData, llm);
const sentences = punctuatedText.match(/[^.!?]+[.!?]+/g) || [punctuatedText];
const words = timestampData.transcription.filter((w: any) => w.text.trim());
// Assign speaker to each sentence
const sentencesWithSpeakers = sentences.map(sentence => {
sentence = sentence.trim();
if(!sentence) return null;
const sentenceWords = sentence.toLowerCase().replace(/[^\w\s]/g, '').split(/\s+/);
const speakerWordCount = new Map<number, number>();
sentenceWords.forEach(sw => {
const word = words.find((w: any) => sw === w.text.trim().toLowerCase().replace(/[^\w]/g, ''));
if(!word) return;
const wordTime = word.offsets.from / 1000;
const speaker = speakers.find((seg: any) => wordTime >= seg.start && wordTime <= seg.end);
if(speaker) {
const spkNum = speakerMap.get(speaker.speaker);
speakerWordCount.set(spkNum, (speakerWordCount.get(spkNum) || 0) + 1);
}
});
let bestSpeaker = 1;
let maxWords = 0;
speakerWordCount.forEach((count, speaker) => {
if(count > maxWords) {
maxWords = count;
bestSpeaker = speaker;
}
});
return {speaker: bestSpeaker, text: sentence};
}).filter(s => s !== null);
// Merge adjacent sentences from same speaker
const merged: Array<{speaker: number, text: string}> = [];
sentencesWithSpeakers.forEach(item => {
const last = merged[merged.length - 1];
if(last && last.speaker === item.speaker) {
last.text += ' ' + item.text;
} else {
merged.push({...item});
}
});
let transcript = merged.map(item => `[Speaker ${item.speaker}]: ${item.text}`).join('\n').trim();
if(!llm) return transcript;
let chunks = this.ai.language.chunk(transcript, 500, 0);
if(chunks.length > 4) chunks = [...chunks.slice(0, 3), <string>chunks.at(-1)];
const names = await this.ai.language.json(chunks.join('\n'), '{1: "Detected Name", 2: "Second Name"}', {
system: 'Use the following transcript to identify speakers. Only identify speakers you are positive about, dont mention speakers you are unsure about in your response',
temperature: 0.1,
});
Object.entries(names).forEach(([speaker, name]) => transcript = transcript.replaceAll(`[Speaker ${speaker}]`, `[${name}]`));
return transcript;
}
private runAsr(file: string, opts: {model?: string, diarization?: boolean} = {}): AbortablePromise<any> {
let proc: any;
const p = new Promise<any>((resolve, reject) => {
@@ -111,102 +226,28 @@ print(json.dumps(segments))
return <any>Object.assign(p, {abort});
}
private async combineSpeakerTranscript(punctuatedText: string, timestampData: any, speakers: any[]): Promise<string> {
const speakerMap = new Map();
let speakerCount = 0;
speakers.forEach((seg: any) => {
if(!speakerMap.has(seg.speaker)) speakerMap.set(seg.speaker, ++speakerCount);
});
const sentences = punctuatedText.match(/[^.!?]+[.!?]+/g) || [punctuatedText];
const lines: string[] = [];
sentences.forEach(sentence => {
sentence = sentence.trim();
if(!sentence) return;
const words = sentence.toLowerCase().replace(/[^\w\s]/g, '').split(/\s+/);
let startTime = Infinity, endTime = 0;
const wordTimings: {start: number, end: number}[] = [];
timestampData.transcription.forEach((word: any) => {
const wordText = word.text.trim().toLowerCase();
if(words.some(w => wordText.includes(w))) {
const start = word.offsets.from / 1000;
const end = word.offsets.to / 1000;
wordTimings.push({start, end});
if(start < startTime) startTime = start;
if(end > endTime) endTime = end;
}
});
if(startTime === Infinity) return;
// Weight by word-level overlap instead of sentence span
const speakerScores = new Map<number, number>();
wordTimings.forEach(wt => {
speakers.forEach((seg: any) => {
const overlap = Math.max(0, Math.min(wt.end, seg.end) - Math.max(wt.start, seg.start));
const duration = wt.end - wt.start;
if(duration > 0) {
const score = overlap / duration; // % of word covered
const spkNum = speakerMap.get(seg.speaker);
speakerScores.set(spkNum, (speakerScores.get(spkNum) || 0) + score);
}
});
});
let bestSpeaker = 1;
let maxScore = 0;
speakerScores.forEach((score, speaker) => {
if(score > maxScore) {
maxScore = score;
bestSpeaker = speaker;
}
});
lines.push(`[Speaker ${bestSpeaker}]: ${sentence}`);
});
return lines.join('\n').trim();
}
asr(file: string, options: { model?: string; diarization?: boolean | 'id' } = {}): AbortablePromise<string | null> {
asr(file: string, options: { model?: string; diarization?: boolean | 'llm' } = {}): AbortablePromise<string | null> {
if(!this.ai.options.whisper) throw new Error('Whisper not configured');
const tmp = join(mkdtempSync(join(tmpdir(), 'audio-')), 'converted.wav');
execSync(`ffmpeg -i "${file}" -ar 16000 -ac 1 -f wav "${tmp}"`, { stdio: 'ignore' });
const clean = () => fs.rm(Path.dirname(tmp), {recursive: true, force: true}).catch(() => {});
const transcript = this.runAsr(tmp, {model: options.model, diarization: false});
const timestamps: any = !options.diarization ? Promise.resolve(null) : this.runAsr(tmp, {model: options.model, diarization: true});
const diarization: any = !options.diarization ? Promise.resolve(null) : this.runDiarization(tmp);
if(!options.diarization) return this.runAsr(tmp, {model: options.model});
const timestamps = this.runAsr(tmp, {model: options.model, diarization: true});
const diarization = this.runDiarization(tmp);
let aborted = false, abort = () => {
aborted = true;
transcript.abort();
timestamps?.abort?.();
diarization?.abort?.();
timestamps.abort();
diarization.abort();
clean();
};
const response = Promise.allSettled([transcript, timestamps, diarization]).then(async ([t, ts, d]) => {
if(t.status == 'rejected') throw new Error('Whisper.cpp punctuated:\n' + t.reason);
const response = Promise.allSettled([timestamps, diarization]).then(async ([ts, d]) => {
if(ts.status == 'rejected') throw new Error('Whisper.cpp timestamps:\n' + ts.reason);
if(d.status == 'rejected') throw new Error('Pyannote:\n' + d.reason);
if(aborted || !options.diarization) return t.value;
let transcript = await this.combineSpeakerTranscript(t.value, ts.value, d.value);
if(!aborted && options.diarization === 'id') {
if(!this.ai.language.defaultModel) throw new Error('Configure an LLM for advanced ASR speaker detection');
let chunks = this.ai.language.chunk(transcript, 500, 0);
if(chunks.length > 4) chunks = [...chunks.slice(0, 3), <string>chunks.at(-1)];
const names = await this.ai.language.json(chunks.join('\n'), '{1: "Detected Name", 2: "Second Name"}', {
system: 'Use the following transcript to identify speakers. Only identify speakers you are positive about, dont mention speakers you are unsure about in your response',
temperature: 0.1,
});
Object.entries(names).forEach(([speaker, name]) => transcript = transcript.replaceAll(`[Speaker ${speaker}]`, `[${name}]`));
}
return transcript;
if(aborted || !options.diarization) return ts.value;
return this.diarizeTranscript(ts.value, d.value, options.diarization == 'llm');
}).finally(() => clean());
return <any>Object.assign(response, {abort});
}

24
src/llm.ts
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@@ -145,7 +145,7 @@ class LLM {
// Handle compression and memory extraction
if(options.compress || options.memory) {
let compressed = null;
let compressed: any = null;
if(options.compress) {
compressed = await this.ai.language.compressHistory(options.history, options.compress.max, options.compress.min, options);
options.history.splice(0, options.history.length, ...compressed.history);
@@ -164,6 +164,15 @@ class LLM {
}), {abort});
}
async code(message: string, options?: LLMRequest): Promise<any> {
const resp = await this.ask(message, {...options, system: [
options?.system,
'Return your response in a code block'
].filter(t => !!t).join(('\n'))});
const codeBlock = /```(?:.+)?\s*([\s\S]*?)```/.exec(resp);
return codeBlock ? codeBlock[1].trim() : null;
}
/**
* Compress chat history to reduce context size
* @param {LLMMessage[]} history Chatlog that will be compressed
@@ -343,14 +352,11 @@ class LLM {
* @returns {Promise<{} | {} | RegExpExecArray | null>}
*/
async json(text: string, schema: string, options?: LLMRequest): Promise<any> {
let resp = await this.ask(text, {...options, system: (options?.system ? `${options.system}\n` : '') + `Only respond using a JSON code block matching this schema:
\`\`\`json
${schema}
\`\`\``});
if(!resp) return {};
const codeBlock = /```(?:.+)?\s*([\s\S]*?)```/.exec(resp);
const jsonStr = codeBlock ? codeBlock[1].trim() : resp;
return JSONAttemptParse(jsonStr, {});
const code = await this.code(text, {...options, system: [
options?.system,
`Only respond using JSON matching this schema:\n\`\`\`json\n${schema}\n\`\`\``
].filter(t => !!t).join('\n')});
return code ? JSONAttemptParse(code, {}) : null;
}
/**

3
tsconfig.json
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@@ -15,6 +15,7 @@
"noEmit": true,
/* Linting */
"strict": true
"strict": true,
"noImplicitAny": false
}
}