whisper-transcription

name	whisper-transcription
description	Transcribe audio/video to text with word-level timestamps using OpenAI Whisper. Use when you need speech-to-text with accurate timing information for each word.

Whisper Transcription

OpenAI Whisper provides accurate speech-to-text with word-level timestamps.

Installation

pip install openai-whisper

Model Selection

Use the tiny model for fast transcription - it's sufficient for most tasks and runs much faster:

Model	Size	Speed	Accuracy
tiny	39 MB	Fastest	Good for clear speech
base	74 MB	Fast	Better accuracy
small	244 MB	Medium	High accuracy

Recommendation: Start with tiny - it handles clear interview/podcast audio well.

Basic Usage with Word Timestamps

import whisper
import json

def transcribe_with_timestamps(audio_path, output_path):
    """
    Transcribe audio and get word-level timestamps.

    Args:
        audio_path: Path to audio/video file
        output_path: Path to save JSON output
    """
    # Use tiny model for speed
    model = whisper.load_model("tiny")

    # Transcribe with word timestamps
    result = model.transcribe(
        audio_path,
        word_timestamps=,
        language=  
    )

    
    words = []
     segment  result[]:
           segment:
             word_info  segment[]:
                words.append({
                    : word_info[].strip(),
                    : word_info[],
                    : word_info[]
                })

     (output_path, )  f:
        json.dump(words, f, indent=)

     words