My Team Works in English and Korean. Here's How I Translate Research Without Losing Nuance.

My role is to keep a cross-language research operation moving — US team producing research in English, Korean partner organization needing that research in Korean, and regular communication flowing in both directions. The translation is infrastructure: it has to work reliably, it can't take two days, and it needs to produce Korean that Korean professionals actually want to read.

What Cross-Language Team Coordination Requires

The translation load in a genuinely bilingual team is larger than it looks from the outside. In a typical week I'm translating:

• Research summaries and reports (English → Korean)
• Meeting agendas and follow-up notes (both directions)
• Slack messages with context-dependent meaning (both directions)
• Presentations for Korean partner organization (English → Korean)
• Korean feedback and questions from partners (Korean → English for US team)

None of this is formal enough to warrant a professional translator for every piece, and the volume is too high for occasional professional translation to keep pace. The workflow I've built needs to handle both directions, in near real-time.

The Register Problem With Korean Translation

Korean business communication is not just translated English. The relationship between sender and recipient determines which speech level to use — and this choice runs through every sentence of every document, because verb endings and vocabulary choices change at each level.

Machine translation defaults to a middle-formal level (합쇼체) that's appropriate for B2B communication with organizations you don't have a close relationship with. For communication with our Korean partners, whom we know well and with whom a slightly less formal register is appropriate, MT output can sound stiff.

My solution: I use Papago as the first pass, then have our Korean partner team lead do a 10-minute register review on anything going to a wide audience. For internal notes and quick messages, I send the Papago output directly — the Korean team prefers faster communication over perfectly calibrated register for routine updates.

"The translation that takes 30 seconds in Papago would take 20 minutes to do manually. The 10-minute register review is worth it for important documents; for routine updates, the Papago output is good enough."

— Wen Lin

Translating Meeting Content

Our video calls with the Korean team run in English (since our Korean colleagues speak English, and the calls are recorded for the US team's reference). But meeting summaries and action items go out in Korean.

My workflow:

1. Record the meeting (Zoom cloud recording)
2. Upload the .mp4 to sipsip.ai's transcriber — select English
3. Get the English transcript + AI summary in about 5 minutes
4. Translate the AI summary into Korean with Papago
5. Expand into meeting notes format in Korean, with action items flagged

The AI summary step is key: it gives me a structured English starting point (3–5 main decisions, action items) that translates cleanly. Translating a full raw transcript is harder to edit into coherent Korean meeting notes; translating a structured summary is fast and produces clean output.

For Research Reports

Our core deliverable is research — English-language analysis that Korean partners need in Korean. These documents are longer (20–50 pages) and need accurate, readable Korean.

My workflow:

For text documents, I use Papago's document translation feature for the first pass, then run sections through DeepL as a comparison for any sentences that read awkwardly. I compare both outputs for technical terminology — Korean technical vocabulary is still evolving for some AI and research methods terms, and the two tools sometimes make different translation choices.

What I watch for:

• English technical terms that should be left in English vs. translated into Korean equivalents. "Machine learning" can stay as "머신러닝" (machine learning, transliterated) or become "기계 학습" (giye haksŭp, translated) — usage varies by context and audience. We've standardized our terminology list.
• Numbers: Korean uses 만 (10,000) and 억 (100,000,000) as base units, while English uses thousands and millions. Reports about market size or research scale need this conversion explicitly.
• Citation format: Korean academic and business documents cite sources differently from English. I adjust citation formatting after translation.

The Korean → English Direction

For content coming from our Korean partners — their research notes, feedback documents, questions — I use Papago for initial translation and read quickly for any register or nuance that seems off. For formal documents they've sent, I translate with both Papago and DeepL and compare.

Korean audio content from our partners (recorded presentations, voice memos) goes through sipsip.ai with Korean selected as the source language. The Korean transcript then goes to Papago for English translation.

Wen Lin is a research operations manager coordinating cross-language research teams between the United States and South Korea. She uses sipsip.ai for meeting transcription and Papago + DeepL for English-Korean document translation in her daily workflow.

Wen Lin

Research Operations Manager

As a research operations manager coordinating work between a US team and Korean partners, I translate English research, meeting notes, and reports into Korean constantly. Getting Korean-language content that reads naturally — not like a translated document — took time to figure out.