How to Extract Audio From Video and Transcribe It With Whisper API

Transcription is the gateway to understanding video content at scale. Once you have timestamped text from a video, you can score segments for virality, generate captions, search across a library of content, or build a summarization layer on top. This post covers the complete implementation: FFmpeg audio extraction, file optimization for Whisper, the API call, and timestamp processing. This transcription pipeline powers the clip selection engine at ClipSpeedAI. Step 1: Extract Audio With FFmpeg Sending the full video file to the Whisper API is wasteful — you pay for processing time and upload time for video data that Whisper ignores. Extract audio first. // lib/audio_extractor.js import { execa } from 'execa'; import path from 'path'; export async function extractAudio(videoPath, options = {}) { const { sampleRate = 16000, // Whisper's native sample rate channels = 1, // mono — stereo adds no value for speech recognition bitrate = '64k', // sufficient for speech; WAV is lossless alterna