Game-Translator
Dynasty Warriors Origin Mod
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LOCALIZATION MOD
WATERMARKED vExperimental-1 Austronesian Lang

Dynasty Warriors Origin Mod Dynasty Warriors Origin Mod

Bahasa Indonesia, Melayu, Filipino

Become immersed in exhilarating battles as a nameless hero in the Three Kingdoms while diving withing cultural nuances of Indonesia, Melayu, or Filipino

Product Narrative

The Full Story

It's finished, i am fully utilize python as binary editor.

Video Logs

Current Milestone

Experimental Build

Author's Notes


Attention: This version contains 6.4% watermarks. Support this project on Trakteer or Ko-fi to download NON-WATERMARKED version.

Comments

Max 2000 chars · 10/hour · Change name via the chat icon

Linguistic Analysis Report

Stylometric Register Analysis

Discourse analysis using Gemma embeddings. Classifies rhetorical register across the corpus to ensure tonal consistency with source narrative assets.

Casual
41.2%
Standard
21.1%
Formal
37.6%
Emotional Spectrum

Emotional tone mapped via dot-product similarity between extracted dialog embeddings and predefined sentiment anchors using zero-shot semantic alignment.

Positive/Warm
31.9%
Stoic/Restrained
30.9%
Negative/Intense
14.8%
Neutral/Functional
13.2%
Complex/Ambivalent
9.1%
Archetypes
30 detected
Xiahou Dun
10.4%
Liu Bei
7.9%
Yuan Shao
7.1%
Wanderer
6.8%
Guo Jia
6.6%
Cao Cao
6.3%
Zhou Yu
5.7%
Guan Yu
4.3%
Zhang Fei
4.0%
Dong Zhuo
2.0%
Lu Bu
2.0%
Sun Quan
1.5%
Zhang Jiao
1.5%
Chen Gong
1.4%
Sun Jian
1.3%
Zhuge Liang
1.3%
Huang Gai
1.2%
Jia Xu
1.2%
Diaochan
1.2%
Xu Shu
1.1%
Zhao Yun
1.0%
???
1.0%
Bailuan
1.0%
Xun Yu
1.0%
Xun You
1.0%
Zhang Liao
0.9%
Zhuhe
0.9%
Npc
0.9%
Sun Shangxiang
0.9%
Zhang He
0.9%

DISCLOSURE: Profiling data generated algorithmically via zero-shot inference and semantic vector alignment. Represents AI interpretation of the dataset corpus, not explicit ground-truth statistics from the underlying game engine or internal metrics. Use as a heuristic guide for context mapping.

Cross-Lingual Quality Matrix

Semantic alignment quantified via Multilingual E5 Large Instruct (RoBERTa based) bitext mining. NER entities preserved using GLiNER heuristic extraction protocols to maintain terminological invariance.

ID
Indonesian
25,780 / 26,026 lines
99%
Semantic Sim.
87 %
Lex. Density
72.0 %
src
62.9%
Lex. Diversity
3.9 %
src
2.6%
MS
Malay
25,818 / 26,026 lines
99%
Semantic Sim.
86 %
Lex. Density
72.7 %
src
62.9%
Lex. Diversity
2.8 %
src
2.6%
TL
Tagalog
25,746 / 26,026 lines
99%
Semantic Sim.
81 %
Lex. Density
60.6 %
src
62.9%
Lex. Diversity
3.6 %
src
2.6%

* Sim = Cosine Similarity (Vector Space) · Density = Content/Total Tokens · Diversity = TTR (Type-Token Ratio) · "src" = Source Baseline · Named Entities enforced via GLiNER mining.

Corpus Volume & Metrics
78,009 Token Lines
Src Density
62.9%
Src Diversity
2.6%
Syntactic Error Report

Heuristic markup verification utilizing multi-pass validation and correction to ensure syntactical integrity of control codes and visual tags.

1526
Mismatch
1526
Fixed
0
Partial

Name

Label
Retrieving Portrait...
Narrative Profile

Associated Entities
Semantic Archetypes

NLP Pipeline Intelligence

Featured Preview Auto-Detected

Line Identity 0
Source (English)
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Indonesian (ID)
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Malay (MS)
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Tagalog (TL)
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Pipeline Receipts

Merger (S7) 2026-02-28 11:57
Tag Repair (S6) 2026-02-28 11:48
Re-Import (S4) 2026-02-28 11:41
Corrector (S3) 2026-02-28 11:02
Validator (S5) 2026-02-28 01:26
Translator (S2) 2026-02-28 00:30
Tagger (S1) 2026-02-27 20:30
Splitter (S0) 2026-02-27 20:16
Corrector (S3) 2026-02-27 13:56
Tagger (S1) 2026-02-27 10:04
Corrector (S3) 2026-02-21 19:17
Re-Import (S4) 2026-02-21 19:17
Tagger (S1) 2026-02-19 23:05

Released Archive

Austronesian Showcase

Location
Image
Video