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Every Southeast Asian professional code-switches. Almost every AI transcription tool fails on it. Here's why — and what's changing.
Your Singapore team is on a call. Someone says: "Eh, so we need to deploy this feature lah, but the database query very slow lor." Try to transcribe it with Otter.ai or Google Meet. You'll get something garbled and wrong. This is code-switching — and it's breaking almost every AI transcription tool on the market.
Read articleA practical guide to what you can and can't do in Singapore, Malaysia, and Indonesia.
It started with a stupid question in a Zoom call. My team was scattered across Singapore, Jakarta, and Kuala Lumpur. Someone suggested we record the meeting for notes. "Sure," I said. Then someone else asked — "Wait, is that even legal?" Nobody knew. I spent three weeks reading through legal frameworks so you don't have to.
Read articleMost AI transcription tools were trained on monolingual speakers. BYSIK was built for the rest of us.
If you work in a Southeast Asian office, you know exactly what your meetings sound like. A sentence starts in English, pivots into Bahasa Indonesia, slips into Tagalog, and lands back in English. All in under 30 seconds. BYSIK's multilingual acoustic model was built for exactly this — handling code-switching as a first-class feature, not an afterthought.
Read articleA deep dive into how accent-inclusive AI training changes transcription accuracy for non-native English speakers.
A 2023 Stanford study found error rates up to 68% higher for non-standard English accents in major speech-to-text tools. For hundreds of millions of professionals across Southeast Asia, this is not a statistic — it is a daily frustration. BYSIK's acoustic model was trained on Indonesian, Filipino, Malaysian, Vietnamese, and Thai English speakers to address this directly.
Read articleThe meeting notetaker built for multilingual reality — capturing what was actually said, not just what the AI could recognize.
Most meeting notetakers fail multilingual teams for a simple reason: every step after transcription assumes the previous one was complete. When half your meeting happens in Bahasa or Tagalog and the tool only captured English, every downstream output — summary, action items, decisions — is missing half the meeting. BYSIK's cross-lingual semantic model fixes this at the foundation.
Read articleWe're writing about AI transcription, multilingual meeting tools, and team productivity in Southeast Asia.