# Transcription DevTools

Includes:
  * __JiWER__ CLI NodeJS wrapper
  * Benchmark tool to test multiple transcription engines
  * TypeScript classes to evaluate word-error-rate of files generated by the transcription

## Build

```sh
npm run build
```

## Benchmark

A benchmark of available __transcribers__ might be run with:
```sh
npm run benchmark
```
```
┌────────────────────────┬───────────────────────┬───────────────────────┬──────────┬────────┬───────────────────────┐
│        (index)         │          WER          │          CER          │ duration │ model  │        engine         │
├────────────────────────┼───────────────────────┼───────────────────────┼──────────┼────────┼───────────────────────┤
│ 5yZGBYqojXe7nuhq1TuHvz │ '28.39506172839506%'  │  '9.62457337883959%'  │  '41s'   │ 'tiny' │   'openai-whisper'    │
│ x6qREJ2AkTU4e5YmvfivQN │ '29.75206611570248%'  │ '10.46195652173913%'  │  '15s'   │ 'tiny' │ 'whisper-ctranslate2' │
└────────────────────────┴───────────────────────┴───────────────────────┴──────────┴────────┴───────────────────────┘
```

The benchmark may be run with multiple model builtin sizes:

```sh
MODELS=tiny,small,large npm run benchmark
```

## Jiwer

> *JiWER is a python tool for computing the word-error-rate of ASR systems.*
> https://jitsi.github.io/jiwer/cli/

__JiWER__ serves as a reference implementation to calculate errors rates between 2 text files:
- WER (Word Error Rate)
- CER (Character Error Rate)


### Usage

```typescript
const jiwerCLI = new JiwerClI('./reference.txt', './hypothesis.txt')

// WER as a percentage, ex: 0.03 -> 3%
console.log(await jiwerCLI.wer())

// CER as a percentage: 0.01 -> 1%
console.log(await jiwerCLI.cer())

// Detailed comparison report
console.log(await jiwerCLI.alignment())
```

## Resources

- https://jitsi.github.io/jiwer/
- https://github.com/rapidfuzz/RapidFuzz