Game-Translator
Persona 3 Reload FEMC MOD
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LOCALIZATION MOD
RELEASED v00 Austronesian Lang

Persona 3 Reload FEMC MOD Persona 3 Reload FEMC MOD

Austronesian Subtitles

Memuat data interpretasi naratif secara real-time...

Product Narrative

The Full Story

Some subtitles is translated, but sometimes not. Albeit that problem, it's finished. I don't have plan to support this MOD.

Current Milestone

Available Now

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
64.8%
Standard
27.1%
Formal
8.0%
Emotional Spectrum

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

Positive/Warm
25.1%
Neutral/Functional
24.2%
Stoic/Restrained
22.0%
Complex/Ambivalent
21.4%
Negative/Intense
7.4%
Archetypes
30 detected
Yukari
19.3%
Shinjiro
10.3%
Chidori
9.5%
Fuuka Yamagishi
9.5%
Aigis
5.6%
Yuko Nishiwaki
3.8%
Junpei
2.7%
Chihiro Fushimi
2.6%
Akihiko
2.5%
Hero
2.5%
Npc
2.1%
Kenji Tomochika
1.9%
Bebe
1.6%
Keisuke Hiraga
1.4%
Shuji Ikutsuki
1.4%
Mr. Edogawa
1.2%
Ryoji
1.2%
Mitsuru
1.1%
Ryoji Mochizuki
1.0%
Nozomi Suemitsu
1.0%
Ms. Toriumi
0.8%
Kazushi Miyamoto
0.8%
Fuuka
0.7%
Igor
0.6%
Elizabeth
0.5%
Koromaru
0.5%
Skilled Reporter
0.4%
Yuko
0.4%
Mamoru Hayase
0.4%
Bunkichi
0.4%

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
27,339 / 27,606 lines
99%
Semantic Sim.
85 %
Lex. Density
73.3 %
src
62.0%
Lex. Diversity
4.8 %
src
3.5%
MS
Malay
27,346 / 27,606 lines
99%
Semantic Sim.
83 %
Lex. Density
72.5 %
src
62.0%
Lex. Diversity
3.5 %
src
3.5%
TL
Tagalog
27,164 / 27,606 lines
98%
Semantic Sim.
80 %
Lex. Density
60.8 %
src
62.0%
Lex. Diversity
5.0 %
src
3.5%

* 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
79,956 Token Lines
Src Density
62.0%
Src Diversity
3.5%
Syntactic Error Report

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

383
Mismatch
383
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) 2026-03-09 12:41
Tag Repair (S6) 2026-03-05 03:03
Validator (S5) 2026-03-05 02:49
Re-Import (S4) 2026-03-05 01:51
Corrector (S3) 2026-03-05 01:04
Translator (S2) 2026-03-05 01:00
Tagger (S1) 2026-03-04 16:54
Splitter (S0) 2026-03-04 16:48

Released Archive

Austronesian Showcase

Location
Image
Video