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

Dynasty Warriors Origin Subtitle Dynasty Warriors Origin Subtitle

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.

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.

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

Video Logs

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 04:57
Tag Repair (S6) 2026-02-28 04:48
Re-Import (S4) 2026-02-28 04:41
Corrector (S3) 2026-02-28 04:02
Validator (S5) 2026-02-27 18:26
Translator (S2) 2026-02-27 17:30
Tagger (S1) 2026-02-27 13:30
Splitter (S0) 2026-02-27 13:16
Corrector (S3) 2026-02-27 06:56
Tagger (S1) 2026-02-27 03:04
Corrector (S3) 2026-02-21 12:17
Re-Import (S4) 2026-02-21 12:17
Tagger (S1) 2026-02-19 16:05

Released Archive

Austronesian Showcase

Location
Image
Video