# Translia

> Translia is an ISO 17100 and ISO 18587 certified language company based in Beijing and Hong Kong, operating two connected practices: (1) multilingual content workflows for global brands — keeping web, product, and support content aligned across markets — and (2) language data production for AI systems, specializing in Asian-language speech data, code-switching audio, transcription validation, and evaluation. Legal entities: Translia Limited (Hong Kong) and 北京传为文化有限公司 (Beijing).

## Services

### Core — Multilingual Web & Product Content
For websites, product pages, landing pages, campaign assets, and customer-facing content that changes often and needs to stay aligned across markets. Includes terminology control, structured review, and ongoing update cycle support. Best for teams managing 5+ markets with weekly or monthly content changes.

### Premium — Brand & Marketing Localization
Cultural adaptation for brand messaging, campaign copy, slogans, investor communications, and executive content. Multiple creative options per key phrase, native-market cultural review, and style guides for consistency. A tagline that resonates in Chinese will often fail in literal English translation — we bridge that gap.

### Support — Knowledge & Help Content
Synchronized multilingual help centers, FAQ pages, in-app help text, chatbot scripts, and support documentation. Maintained at the pace of product updates so multilingual versions never fall behind source.

### Live — Interpreting & Live Subtitles
Professional consecutive and simultaneous interpreting, real-time subtitle display for presentations, pre-event rehearsal and coordination. Both onsite and remote options for international board meetings, conferences, product launches, and company town halls.

## AI Language Data

Translia builds training and evaluation data for AI, specializing in Asian languages and code-switching — the scenarios general data vendors struggle to source. Managed production (not anonymous crowd labor), with documented consent and provenance per contributor. Four data lines:

- **Speech Data Collection** — scripted and spontaneous speech, dual-speaker conversational, dialectal; managed speaker sourcing with strict technical specs (sample rate, channels, environment, demographics), validated per batch.
- **Code-Switching Audio** — fourteen code-switching locales, seven in production today: Cantonese-English (Hong Kong), Mandarin-English (Mainland), Taiwan Mandarin-English, Japanese-English, Korean-English, Tagalog-English (Taglish), Turkish-English. Seven more ready to activate: Hindi-English (Hinglish), Malay-English, Tamil-English, Indonesian-English, Thai-English, Vietnamese-English, Gulf Arabic-English. Voice AI still fails on code-switched speech — and crowd platforms cannot source it reliably, because natural code-switchers are not findable by filtering on "native language". Translia runs managed native-speaker teams across seven code-switching locales in production today, with seven more ready to activate, each with documented consent and provenance per contributor. Scripted, spontaneous, and dual-speaker conversational formats supported; free pilot batch available. How to evaluate any ASR system for code-switched speech: benchmark on real code-switched audio from the target locale (not vendor demo sets), score accuracy at language-switch points rather than sentence-average word error rate, and check whether the system can be adapted with natural code-switched audio — without that, current accuracy is the ceiling. Translia supplies the benchmark and adaptation data behind that evaluation.
- **Transcription & Validation** — multi-language transcription and validation QA at production scale, per-batch turnaround.
- **MT & LLM Evaluation** — adequacy, fluency, ranking, and LQA by native evaluators.

Languages include Hong Kong Cantonese, Taiwan Mandarin, Simplified Mandarin and other Chinese variants, Korean, Japanese, Filipino, Turkish, and a growing set. Engagement model is company-to-company, including as a subcontracted production partner to leading AI platform providers. Provenance-first production: documented consent, sourcing and batch records supporting AI-regulation transparency requirements (e.g. EU AI Act). See [AI Data services](https://www.translia.com/en/data).

- [Asian-language capacity by locale](https://www.translia.com/en/data/asian-languages/): which Asian locales are production-proven (delivered production batches) versus ready to activate, and what work each has delivered; capacity means people Translia can field, not database size
- [For vendor managers at MLVs and AI data companies](https://www.translia.com/en/data/vendors/): AI data work delivered as a subcontractor (transcription validation, speech recording, annotation and scoring, in-market testing), how a batch runs inside a vendor's workflow, and supplier-onboarding materials. No off-the-shelf datasets for licensing.

## Service detail pages

- [Website Localization](https://www.translia.com/en/services/website-localization/): multilingual website localization kept aligned as source content changes
- [Multimedia Localization](https://www.translia.com/en/services/multimedia-localization/): subtitling, voiceover/dubbing, audio and video localization
- [Interpreting](https://www.translia.com/en/services/interpreting/): simultaneous and consecutive interpreting, live subtitles, onsite and remote
- [Game & Manga Localization](https://www.translia.com/en/services/game-localization/): in-game text/UI and manga, anime, and comic translation
- [Human Review of AI Translation](https://www.translia.com/en/services/ai-translation-review/): ISO 18587-certified post-editing (MTPE) and LQA evaluation of AI-generated translations, against MQM/DQF-based or client-defined error frameworks — human layer only, no technology bundle

## Industries

- [Automotive & EV](https://www.translia.com/en/industries/automotive-ev-localization/): infotainment UI, owner's manuals, safety and regulatory documentation for automotive/EV brands going global
- [Aviation](https://www.translia.com/en/industries/aviation/): airline websites, in-flight content, safety and regulatory manuals, and audit materials

## Work with us

- [Join the linguist network](https://www.translia.com/en/join): remote, per-task work for native-speaker transcribers, recorders, and reviewers

## About

Translia is headquartered in Beijing and Hong Kong, serving enterprise clients globally. Primary markets: China-origin brands expanding internationally, and international brands entering Chinese-speaking markets.

Legal entities: 北京传为文化有限公司 (Beijing) and Translia Limited (Hong Kong).

Languages served: Chinese (Simplified and Traditional), English, French, and other major languages.

## Key pages

- [Services](https://www.translia.com/en/services): All four service lines with full scope details
- [AI Data](https://www.translia.com/en/data): Language data for AI — speech, code-switching, transcription validation, evaluation
- [How We Work](https://www.translia.com/en/how): Content workflow methodology and delivery process
- [Industries](https://www.translia.com/en/industries): Consumer electronics, cross-border e-commerce, software & SaaS, professional services
- [Insights](https://www.translia.com/en/insights/): Articles on multilingual content strategy, workflow design, and localization operations
- [Contact / Free Workflow Assessment](https://www.translia.com/en/contact): Share your current setup; we identify where you're losing time to review drag, language drift, and coordination overhead — free

- [About Translia](https://www.translia.com/en/about): Company background, certifications (ISO 17100, ISO 18587), legal entities and the two connected practices — multilingual content workflows and AI language data.
## Chinese (Simplified)

- [服务](https://www.translia.com/cn/services)
- [AI 数据](https://www.translia.com/cn/data)
- [交付方式](https://www.translia.com/cn/how)
- [行业方案](https://www.translia.com/cn/industries)
- [洞察](https://www.translia.com/cn/insights/)
- [加入我们（译员招募）](https://www.translia.com/cn/join)
- [联系我们](https://www.translia.com/cn/contact)

## French

- [Services](https://www.translia.com/fr/services)
- [Méthode](https://www.translia.com/fr/how)
- [Secteurs](https://www.translia.com/fr/industries)
- [Insights](https://www.translia.com/fr/insights/)
- [Nous contacter](https://www.translia.com/fr/contact)

## Contact

Email: hi@translia.com
Beijing: +86-(0)10-67122138 · B110, DoBe WE International Hub, No.91 Fahuasi Street, Dongcheng District, Beijing 100061, China
Hong Kong: +852-4407-2994 · 2/F, Lee Fung Commercial Building, 32-36 Des Voeux Rd W, Sheung Wan, Hong Kong

## Insights — English

Articles on multilingual content strategy, workflow design, and localization operations.

- [Automotive distributors don't own the source content — and that is the localization problem](https://www.translia.com/en/insights/automotive-distributor-inherited-content/): Importers and official distributors localize vehicle content they did not write, on a release cycle they do not control. The failure is inheritance, not translation: manuals, HMI strings and compliance text arrive from separate upstream teams with no channel signalling what changed, so the same component acquires three names across artifacts. The three decisions that are cheap before launch and expensive after — one terminology base owned by the distributor across all inherited artifacts, a named source-change channel, and regulatory review separated from translation, since a faithful translation of a source written for another regulatory regime can be linguistically correct and still non-compliant.
- [Localization testing checklist: 27 checks before a multilingual site ships](https://www.translia.com/en/insights/localization-testing-checklist/): Internationalization testing asks whether the build can support any locale and runs once on the codebase before translation; localization testing asks whether this locale is right and runs per language on the built site afterwards. Collapsing them into one step is why the same structural bugs recur every launch. 27 checks across five layers — i18n readiness, language in context, layout and typography under text expansion, functional and data formats, and the pre-launch pass. Most post-launch localization bugs are integration defects, not translation defects: correct text placed into a layout, format or code path never verified in that locale. A pseudo-localization pass before any translation exists surfaces hardcoded strings, truncation points and layout breaks in a single sweep.
- [How to evaluate AI translation quality: what a working error framework looks like](https://www.translia.com/en/insights/how-to-evaluate-ai-translation-quality/): "Reads fine" is not evaluation. Quality is scored against a defined error framework — MQM/DQF categories covering accuracy, fluency, terminology, style and locale conventions, each with severity weighting — on a sampling cadence matched to volume, with corrections fed back into the glossary and the engine choice. Covers how to build the framework, how much to sample, what to report, and how to choose between light post-editing, full post-editing and LQA-only monitoring.
- [Can you train on public code-switching data? What the corpora actually contain](https://www.translia.com/en/insights/public-code-switching-datasets/): Three language pairs account for roughly 76% of code-switching ASR research — Mandarin-English alone about 55%, Hindi-English about 11%, Bengali-English about 3% (Agro et al., arXiv:2507.07741). For Mandarin-English public data genuinely exists: TALCS 587 hours spontaneous, SEAME 192 hours, ASCEND 10.6 hours, and ASRU 2019 at 740 hours which is read rather than spontaneous. Outside those pairs the numbers collapse to between two and fifteen hours — enough to evaluate a system, not to adapt one. The broadest multilingual set, CS-FLEURS (Interspeech 2025), covers 113 code-switched pairs across 52 languages and 300 hours, but every subset is read speech or text-to-speech: not one of the 113 pairs is a recording of someone code-switching in conversation. The ASCEND paper states the field's own problem directly — most existing work collects code-switching data from read speech rather than spontaneous speech, and switch placement, density and hesitation all differ between the two. Practical consequence: public corpora usually yield an evaluation set, rarely adaptation data, because adaptation data has to match the buyer's scenario, register, market variety and vintage.
- [Code-switching speech data: why it's the frontier multilingual AI can't skip](https://www.translia.com/en/insights/code-switching-speech-data-frontier/): Code-switching — mixing two languages inside one sentence, as in Cantonese-English service calls or Mandarin-English office speech — is everyday language for hundreds of millions of people and the point where ASR and voice AI still break. The training data cannot be scraped from the web or reliably synthesized at quality: it has to be recorded to specification by real bilingual speakers, with consent and provenance documented.
- [In-house team or translation vendor: the thresholds where the answer changes](https://www.translia.com/en/insights/in-house-team-or-translation-vendor/): "We have an in-house team" covers three different setups: a dedicated localization function (a vendor adds capacity and language coverage, not competence), bilingual employees doing it alongside another job (by far the most common, and described using the language of the first), and a coordinator who routes work without producing it. Keeping it internal is genuinely right with one or two languages and stable content, for internal-only material, where domain knowledge outweighs writing craft, or where speed matters more than polish. Four thresholds mark where it stops working: language count past three or four (coordination becomes a job of its own), updates monthly or faster (a project turned into an operation with nobody assigned to operate it), external exposure — claims, contracts, safety, regulated labelling (the translator is also the approver and no one else reads it), and the cost of a senior person's attention. The internal option wins cost comparisons automatically because it is the only one without an invoice: half a day a month is six working days a year that appear in no budget line, so count hours actually spent for one month before deciding. Being a native speaker is a prerequisite, not a qualification — it makes someone an excellent reviewer, not necessarily a writer in a register they do not work in, which is why the common failure is accurate text that reads as translated. The configuration that usually wins past the thresholds keeps review inside, where product knowledge and claim limits live, and moves production out — and it fails in exactly one way, when review has no named owner, no written criterion and no decided default for silence.
- [Enforcing translation review before publish: what a gate can and cannot do](https://www.translia.com/en/insights/translation-review-approval-gate/): An approval gate fails less often because someone skipped review than because it had a single owner with another full-time job, became a queue, and got routed around by people holding a launch date. Three gate shapes and what each suits: blocking (regulated, legal and safety text, pricing, brand claims), advisory (high-volume low-risk content — the notification goes unread and drift accumulates invisibly), and sampled (most marketing and product content — the sample gets picked by convenience rather than risk). Choose per content type, not per project. A TMS or CMS workflow genuinely enforces that nothing publishes without a recorded approval, who may approve by role and locale, an audit trail, and escalation past a threshold — but no tool supplies authority, the criterion the reviewer checks against, or availability when the reviewer is on holiday; buying the mechanism alone produces an audited bottleneck. Four decisions keep the gate from becoming the bottleneck: separate must-approve from must-be-informed, give every gate a deputy, decide in writing what happens by default when the review window expires, and measure time in queue rather than pass rate — 98% approval with a nine-day median means the gate is being avoided or rubber-stamped.
- [How to prevent locale drift: keeping source and localized content in sync](https://www.translia.com/en/insights/how-to-prevent-locale-drift/): The five workflow controls — single source of truth, enforced terminology, per-locale review ownership, update propagation, and version records — that keep localized content aligned as the source changes.
- [Keeping game terminology consistent across every asset and update](https://www.translia.com/en/insights/game-localization-terminology-consistency/): Why game terminology consistency across UI, dialogue, store, marketing, and future patches depends on a maintained termbase and update workflow, not individual translators.
- [Going global was a price war. It's becoming a rules war — and content is the battleground.](https://www.translia.com/en/insights/going-global-is-a-rules-war/): Why the compliance layer of going global is made of multilingual content — regulatory terminology, market-specific adaptation, update propagation, and audit-ready records — and how the same provenance shift is arriving in AI.
- [Transcription validation is a workflow problem, not a listening problem](https://www.translia.com/en/insights/transcription-validation-workflow/): Why the quality of validated speech data for AI is decided by the workflow around the listeners — reference checks, variant guides, effort tracking, correction memory — not careful listening alone.
- [The language vendor decision BPOs keep deferring — and what it costs](https://www.translia.com/en/insights/bpo-language-vendor-consolidation/): Why fragmented, program-by-program language sourcing inside BPOs is an ownerless cost center, and what consolidating to one accountable vendor actually buys.
- [Who owns your translation memory? The clauses to settle before you sign a TMS or vendor contract](https://www.translia.com/en/insights/who-owns-your-translation-memory/): Translation memory and termbases are the localization assets that keep paying back, and contracts with a TMS or language vendor rarely say who owns them. Five clauses to settle before signing: ownership stated plainly regardless of host; export in open formats (TMX for memory, TBX for terminology) with locale codes, segment status, dates and context, since text-only pairs are legally yours but practically diminished; routine quarterly exports rather than an exit-only right; separation from other clients' material, since pooled memories are a legitimate choice only if made knowingly; and ownership of derived assets, including machine translation engines adapted on your content. The test: request a full export before you need it and check segment count, locale-code consistency and that recent approved segments keep their status. What protects the asset is the contract and the export habit, not whether the supplier is a platform or a managed service; a per-word rate lowered by memory reuse is only a saving if the memory stays yours.
- [Translation agency or TMS? What enterprise teams actually need to decide](https://www.translia.com/en/insights/translation-agency-or-tms-what-enterprise-teams-need/): How enterprise teams decide between translation agencies and TMS platforms — and why the right answer depends on what they actually lack.
- [Website localization checklist: what enterprise teams miss before their first multilingual launch](https://www.translia.com/en/insights/website-localization-checklist/): The specific checks that prevent rework, misaligned versions, and post-launch corrections for teams launching multilingual websites.
- [The AI voice you talk to was trained by humans. That part is getting harder, not easier.](https://www.translia.com/en/insights/ai-voice-trained-by-humans/): Why multilingual AI voice quality depends on human language labor, and why that labor is becoming harder to source well.
- [What AI translation still gets wrong — and why the next challenge is orchestration, not generation](https://www.translia.com/en/insights/what-ai-translation-still-gets-wrong/): The limits of current AI translation and why enterprise teams need orchestration, not just generation.
- [Smart outdoor brands are winning product awards. Their content still reads like spec sheets.](https://www.translia.com/en/insights/smart-outdoor-brands-content-gap/): Why outdoor and adventure brands lose conversion to content that fails to match product experience to audience expectations.
- [Why BPO delivery teams lose control of multilingual quality before they lose control of volume](https://www.translia.com/en/insights/bpo-delivery-teams-lose-control-of-multilingual-quality/): How multilingual quality degrades in BPO environments and what structural fixes actually work.
- [Product pages are becoming regulated data surfaces, not just marketing pages](https://www.translia.com/en/insights/product-pages-are-becoming-regulated-data-surfaces/): How EU digital product regulations are turning product content into a compliance surface for multilingual teams.
- [Chinese auto brands can enter Europe fast. Multilingual service readiness is harder to build.](https://www.translia.com/en/insights/europe-launch-needs-multilingual-service-readiness/): Why Chinese automotive brands entering Europe face a multilingual service readiness gap that market entry speed cannot close.
- [Why multilingual website updates create more rework than teams expect](https://www.translia.com/en/insights/why-multilingual-website-updates-create-rework/): The structural reasons multilingual web updates generate disproportionate rework — and how teams reduce it.
- [Cross-border selling got easier. Managing multilingual content for the long run did not.](https://www.translia.com/en/insights/cross-border-selling-still-needs-content-control/): Why AI has lowered the barrier to cross-border entry but not the cost of keeping multilingual content aligned over time.
- ["International communication" is not just a cultural-sector issue for Chinese companies](https://www.translia.com/en/insights/international-communication-is-not-just-cultural-export/): Why Chinese enterprises need structured multilingual content operations, not just translation of marketing materials.
- [What enterprise teams actually need from translation partners — and what most vendors miss](https://www.translia.com/en/insights/what-businesses-actually-need-from-translation-partners/): The gap between what enterprise teams need from language vendors and what traditional translation agencies actually deliver.
- [Auto export 2.0 is creating a multilingual content operations problem, not just a translation one](https://www.translia.com/en/insights/auto-export-needs-multilingual-content-operations/): How the second wave of Chinese auto export is creating content operations challenges that translation alone cannot solve.
- [What second-layer language review catches that standard TMS quality checks miss](https://www.translia.com/en/insights/what-second-layer-review-catches-after-standard-qa/): Why rule-based TMS QA misses semantic drift, tone mismatch, and contextual inconsistency — and what second-layer review adds.
- [Why multilingual content workflows break down before translation quality does](https://www.translia.com/en/insights/why-content-workflows-break-before-translation-does/): How workflow failures — version drift, unclear ownership, repeated review — create multilingual problems before translation quality ever becomes the issue.
- [Why human judgment still defines the outcome in high-stakes multilingual decisions](https://www.translia.com/en/insights/why-human-judgment-still-defines-high-stakes-multilingual-work/): Why experienced human reviewers remain essential for brand, regulatory, and high-stakes multilingual content despite AI advances.
- [CTC and certified translation solve different problems in market entry](https://www.translia.com/en/insights/ctc-vs-certified-translation-market-entry/): The difference between China Trade Certificate (CTC) translation and certified/notarized translation, and which market entry scenarios require each.
- [The localization "impossible triangle" usually means the system is wrong](https://www.translia.com/en/insights/localization-impossible-triangle-needs-better-systems/): Why the localization quality-speed-cost trade-off is often a systems problem, not a vendor problem.
- [Smart robotics companies going global need more than product translation](https://www.translia.com/en/insights/smart-robots-going-global-need-more-than-translation/): Why robotics and smart hardware companies entering global markets need content operations, not just translated product specs.

## Frequently Asked Questions

### What is a multilingual content workflow?
A multilingual content workflow is the end-to-end process of updating source content and keeping all language versions synchronized — covering translation, review, terminology control, file handling, and delivery. Most teams have a translation step but lack the surrounding workflow structure, which causes version drift, rework, and coordination overhead.

### How is Translia different from a traditional translation agency?
Traditional agencies focus on one-time translation projects. Translia is structured around ongoing content operations — recurring update cycles, terminology management, and integration into your existing content publishing workflow. We measure success by how smoothly your multilingual content runs, not by word counts.

### What languages does Translia work with?
Primarily Chinese (Simplified and Traditional), English, and French, with coverage across other major world languages. Our core operational strength is Chinese–English and Chinese–French workflows.

### How does Translia handle terminology consistency across markets?
We maintain client-specific glossaries and style guides. All content is reviewed against these references before delivery, and terminology is updated collaboratively as products and brands evolve.

### Does Translia work with specific industries?
Yes. Primary industries: consumer electronics, cross-border e-commerce, software & SaaS, professional services, and enterprise technology. See /en/industries for sector-specific information.

### What is the free workflow assessment?
A no-cost review of your current multilingual content setup. Share how your team handles updates across languages and we'll identify where you're losing time — specifically to review drag, language drift between markets, and coordination overhead. Followed by a 30-minute call to walk through findings. Available at /en/contact.