I spent three years as a research assistant in a political science department, and part of my job was transcribing interviews. Policy experts, former government officials, activists, academics — people who spoke quickly, used jargon casually, and often overlapped their own sentences in ways that made transcription feel like solving a puzzle with missing pieces.
That was before AI transcription was a good thing. We used a service that charged by the minute and turned audio around in 48 hours, and the quality was... acceptable. Maybe 85% of the words were right. The remaining 15% required someone who understood the subject matter to fix. Which usually meant me, replaying the same 10-second clip for the fifth time trying to figure out whether the interviewee said "bilateral framework" or "lateral framework."
The audio quality problem is not what you think
Conference rooms are terrible for audio. HVAC humming, laptop fans, chairs squeaking, phones buzzing on silent (which actually makes a distinct noise), someone clearing their throat every 45 seconds. The person speaking might be three feet from the microphone or thirty feet. They might be facing the mic or the window. They might drop to almost a murmur because they're making a sensitive point.
And then you want to transcribe this. In two languages. Accurately enough to quote in published research or legal proceedings. That's a hard problem, and it's not purely a technology problem.
What I've seen go wrong
The worst failure I personally witnessed: academic conference in Montreal, 2019. Panels in English and French, bilingual proceedings promised. The service advertised 98% accuracy. Large hall, ceiling mics, no individual speaker microphones. The transcription rendered audience questions from the back as approximately twelve words, half wrong. One paper cited a quote from those proceedings that I'm fairly confident the speaker never said. The words were sort of right. The meaning was different.
This is the dangerous zone. Not the obviously wrong parts — those get caught. It's the almost-right parts that slip through.
Specialized language
Academic interviews use phrases like "epistemic closure within regulatory networks" the way you or I would say "the weather's nice today." AI handles about 80% of the vocabulary well. But specialized terms used idiosyncratically — an economist's "the multiplier" meaning fiscal, monetary, or export depending on five minutes of prior context — still need human understanding of content, not just language.
Confidentiality
Interview and conference transcripts often contain confidential information. Business strategy discussions. Legal proceedings. Medical research under IRB protocols. Confidential document translation isn't just about encrypted files — it's the entire chain: who has access to the audio, where files are stored, whether the system processes on-device or uploads to a cloud that might retain copies.
A client once needed transcripts of executive M&A strategy meetings. The transcripts were essentially confidential documents. They initially wanted a popular AI transcription service. We walked them through data processing implications: audio destination, retention policies, model training usage. They went with on-premise. Cost more. Gave them compliance documentation.
Multilingual complexity
International conferences involve code-switching. Speakers present in English but drop into native language for terms, cultural references, emotional moments. A keynote in Singapore referenced Chinese idioms in Mandarin then explained them in English. The transcription captured the explanations, not the originals. The idioms were the actual point.
Good multilingual transcription captures both languages, with speaker-language tags, reviewed by people who are actually bilingual. Slow and expensive. The only way to get it right.
What actually works
Get the audio right first. Dedicated microphones, not ceiling mics. Recording device at the table, not a phone in a pocket. AI transcription for the first pass. Domain-expert review, not generic editing. For multilingual content, systems that handle code-switching reviewed by truly bilingual people. For confidential content, figure out data handling before you start recording.
At Artlangs Translation, multilingual transcription combines AI speed for the initial pass with human expertise for review. Not in the model — in the person who understands both what was said and what was meant. Across 230+ languages.
