Why Most AI Transcription Tools Fall Short (And What to Use Instead)

Many AI transcription tools struggle with complex audio. I discovered this while helping podcasters transcribe their episodes.

The problem isn't just accuracy anymore. Many popular transcribers miss context switches or struggle with multiple speakers. Through my testing, I've found that combining multiple tools gives better results. I now use a three-step approach: running audio through Whisper first, cross-checking with Rev.ai, and finally using Assembly AI for technical content.

The real game-changer? Looking for transcription tools that handle speaker diarization and timestamps - keeping conversations organized and easily navigable. These are features many tools overlook.

December 12, 2024