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AI Localization & MTPE

KI-Lokalisierung & mehrsprachiges Content-Management

Enterprise AI localization combining domain LLMs, neural machine translation (NMT), terminology constraint filters, and professional human post-editing (MTPE).

Gegenseitige NDA · Mehrstufige Prüfung und QA
KI-Lokalisierung & mehrsprachiges Content-Management
KI-Lokalisierung & mehrsprachiges Content-Management ISO-17100-QA-Standards

Projektvorbereitung

Diese Angaben helfen bei Scope, Zeitplan und Angebot.

01

Source Files

Provide source documents or corpus packages (Word, Excel, XLIFF, JSON, Markdown, PDF).

02

Target Languages

Specify target language pairs and regional audience standards.

03

Purpose & Audience

Clarify use case (internal knowledge base, e-commerce, tech guides, publication).

04

Terminology & References

Provide translation memories (TMX), glossaries (TBX), or prompt constraint rules.

05

Format & Timeline

Confirm quality level (Light MTPE vs Full MTPE), file formats, and delivery schedule.

💡 Note: For high-volume projects, a 1,000-2,000 word pilot sample evaluates MT engine quality and PE effort.

AI + Human Post-Editing (MTPE) Workflow

Corpus pre-processing, engine alignment, human expert post-editing, and TM archival.

01
Stage 01

Parsing & Term Injection

Parse text structures, isolate code tags, and inject glossary terms into model prompts.

02
Stage 02

Engine Machine Translation

Execute high-throughput translation via domain LLMs and NMT while protecting variables.

03
Stage 03

Automated QA Validation

Run automated checks for missing placeholders, numbers, tag corruptions, and term locks.

04
Stage 04

Human Post-Editing (Full MTPE)

Domain linguists review sentence-by-sentence to eliminate machine tone and ensure fluency.

05
Stage 05

Private TM Asset Archival

Final post-edited segments are archived into customer translation memories.

Deliverables

  • Final formatted documents post-edited to human publication standards (Full MTPE)
  • Post-editing effort and edit distance analysis report
  • Updated private translation memories (TMX) and termbases (TBX)
  • Automated QA compliance and consistency logs

Prerequisites & Scope Notes

  • Post-Editing Tiers: Light MTPE focuses on accuracy; Full MTPE delivers native publication fluency
  • Source Text Quality: Garbled source text requires pre-translation cleaning to prevent MT errors
  • Data Privacy: Processed via enterprise zero-data-retention APIs; never used for public LLM training
  • DTP Formatting: Complex CAD drawings and multi-column manuals integrate with DTP engineering

AI Translation & MTPE Technical Sample

Demonstrating raw machine translation output vs specialized human post-editing refinement.

Alle Beispiele →
AI Translation & MTPE Technical Sample EN ➔ ZH-CN
Source (EN - Complex Technical Spec)

"Ensure the fail-safe interlock triggers a controlled shutdown whenever the differential pressure transducer reports an out-of-spec reading across the manifold."

Full MTPE Target (ZH-CN - Post-Edited by Domain Specialist)

“务必确保:一旦压差变送器检测到歧管两端读数超出规格,故障安全联锁装置即刻触发受控停机。”

Raw MT (Draft Flaw) Full MTPE (Human Polish) Post-Editing Rationale
Literal: "Trigger controlled closing..." Controlled shutdown Industry standard: Converts awkward literal phrasing into established technical command
Literal: "Pressure transducer reports..." Differential pressure transmitter GB/T Instrument Terminology: Standardizes transducer to transmitter in fluid systems
Literal: "Across the main pipe everywhere" Across the manifold Fluid mechanics context: Accurate spatial engineering translation of manifold reading
Referenzbeispiel Sample ID: AI-MTPE-01

Chemical Fluid Control System O&M Manual

Service: AI Translation Post-Editing (Full MTPE) · Domain: Process Engineering

1

Eliminating MT Syntactic Artifacts

Restructuring nested English clauses into clear engineering condition-action statements.

2

Domain Term Correction

Fixing generic LLM mistranslations of instrumentation, valves, and piping terms.

3

Productivity Acceleration

2.5x throughput gain over traditional workflows while preserving human publication quality.

FAQ

Häufige Fragen

Preise, Fristen, Vertraulichkeit und Dateiformate—bei weiteren Fragen kontaktieren Sie uns.

Typische Einsatzgebiete für KI-Lokalisierung & mehrsprachiges Content-Management?
Markteintritt, Compliance, Produktlaunches und Business-Kommunikation mit passenden Linguisten.
Wie starten wir ein KI-Lokalisierung & mehrsprachiges Content-Management-Projekt?
Muster, Sprachpaare und Frist senden—PM antwortet innerhalb von 24 Stunden.
Was kostet KI-Lokalisierung & mehrsprachiges Content-Management?
Preis nach Umfang, Sprachpaar, Fachgebiet, Frist und Format. Muster senden—Antwort innerhalb von 24 Stunden.
Welche Faktoren beeinflussen den Preis?
Sprachpaar, Inhaltstyp, DTP, Beglaubigung, Glossar, Eiligkeit und Projektvolumen.
Wie lange dauert die Lieferung?
Ca. 2.000–3.000 Quellwörter pro Tag bei Dokumenten; phasenweise bei Web/Software.
Eilaufträge möglich?
Ja, mit zusätzlichen Ressourcen und Prioritätsplanung. Bitte Frist angeben.

Bereit für Ihr Projekt?

Senden Sie Anforderungen und Dateien. Transparentes Angebot und Zeitplan innerhalb von 24 Stunden.

Gegenseitige NDA möglich
Bewertung innerhalb von 24 Stunden
Transparente Preise & Scope

Bereit für Ihr KI-Lokalisierung & mehrsprachiges Content-Management-Projekt?

Senden Sie Unterlagen für eine passende Bewertung und ein Angebot.

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