Transcription & Analysis
Speech-to-text is solved. The real power is what you do with the words after.
What You'll Learn
- State-of-the-art transcription tools and when to use each
- Speaker diarization — who said what and when
- Extracting insights from conversations at scale
- Building searchable audio archives and knowledge bases
Transcription Is a Solved Problem
OpenAI's Whisper changed everything. Released as open-source in 2022, it achieved near-human accuracy across 99 languages. Suddenly, transcription that used to cost dollars per minute became essentially free. Every tool in this space either uses Whisper directly or competes with it.
Accuracy on clean audio in major languages is 95-99%. The remaining challenges are accents, overlapping speakers, domain-specific jargon, and noisy environments. Knowing which tool handles which edge case is the real skill.
The Transcription Stack
Whisper (local): Free. Run it on your machine. No data leaves your computer. Best for privacy-sensitive content. Slower than cloud options but you control everything.
Deepgram: Fastest cloud transcription. Real-time streaming support. Excellent speaker diarization. Their Nova-2 model rivals Whisper's accuracy at 10x the speed. Pay-per-minute pricing.
AssemblyAI: Best for analysis features beyond raw transcription. Sentiment analysis, topic detection, content moderation, PII redaction — all built in. Their Universal model handles challenging audio well.
Descript: Transcription plus editing in one interface. Edit audio by editing text. Remove filler words with a click. Best for content creators who need transcripts and polished audio simultaneously.
Audio Intelligence
Transcription is step one. The real value comes from what you extract:
Speaker Diarization: Identifying who spoke when. Critical for meetings, interviews, and multi-person recordings. Deepgram and AssemblyAI both handle this well. The output tags each segment with a speaker label.
Sentiment Analysis: Detecting emotional tone throughout a conversation. When did the mood shift? Where did frustration appear? Invaluable for customer call analysis, therapy research, and UX interviews.
Topic Extraction: Automatically identifying what was discussed and when. Turn a two-hour meeting into a structured summary with action items. Feed the transcript to Claude for deeper analysis — "What decisions were made? What questions went unanswered?"
Searchable Archives: Transcribe your entire audio library. Index it. Now you can search across hundreds of hours of recordings by keyword. Your meeting notes, podcast episodes, voice memos — all searchable in seconds.
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