Game-Translator
Darkest Dungeon
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LOCALIZATION MOD
RELEASED vv1.0.0 Austronesian Lang

Darkest Dungeon Darkest Dungeon

Darkest Dungeon Subtitle

Bahasa Indonesia, Melayu, Filipino

Product Narrative

The Full Story

Halo kawan-kawan penjelajah kegelapan! Penat nggak sih main game seseru Darkest Dungeon tapi giliran baca teks dialognya malah kaku banget kayak terjemahan Google Translate jadul? Masa lagi panik kena serangan jantung di dungeon, bahasanya malah kayak robot kekurangan oli? Nah, sekarang saatnya buang jauh-jauh rasa frustrasi itu! Mod lokalisasi ini dibikin khusus buat kamu gamer di Indonesia, Malaysia, dan Filipina lewat 8-stage neural pipeline canggih yang membedah lebih dari 98.000 kata. Si Ancestor (Narator) tetap bakal ngomong puitis dan megah tanpa kata kasar, sedangkan para hero kamu bakal mengumpat dan berdoa pakai gaya bahasa lokal yang alami banget di Indonesia, Malaysia, dan Filipina. UI juga dijamin rapi jali karena 81 error kode tag sudah kami bersihkan secara otomatis. Cocok buat versi Steam original maupun repack, yuk download sekarang!

Current Milestone

Available Now

Author's Notes

=== Audit Teknis & Semantik Lokalisasi DARKEST DUNGEON === 1. SKALA LINGUISTIK & CAKUPAN - Skala Proyek: Sekitar 98,711 kata diproses melalui alur neural 8-tahap. - Cakupan Bahasa: Dukungan trilingual penuh untuk pasar Indonesia, Malaysia, dan Filipina. - Status Kelengkapan: Indonesia: 97.7%, Malay: 97.9%, Filipino: 97.0% - Analisis Variasi Leksikal: Source -> Density: 66.1% | Diversity: 9.5%, Indonesia -> Density: 73.6% | Diversity: 10.3%, Malay -> Density: 73.6% | Diversity: 8.9%, Filipino -> Density: 59.8% | Diversity: 9.2% 2. VALIDASI NEURAL & AKURASI - Skor Keselarasan Semantik (Platt Score): (Skor ini mengukur seberapa akurat terjemahan mempertahankan makna asli dari teks sumber.) - Gaya Bahasa Karakter: Penyesuaian gaya (gaul, formal, santai) telah diterapkan pada 21 karakter unik. - Pemulihan Struktur Otomatis (Tag Repair): 81 tag kode game telah dipulihkan secara presisi. 3. KAPABILITAS ENGINE - Pipeline: Austronesian Localization System (Neural LoRA-Adaptive Architecture). - Pengenalan Entitas: Ekstraksi penuh untuk terminologi spesifik game dan konstanta lore.

Direct Download versi tanpa watermark khusus donatur Trakteer aktif.

Comments

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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
49.6%
Standard
32.1%
Formal
18.3%
Emotional Spectrum

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

Stoic/Restrained
37.3%
Negative/Intense
29.1%
Complex/Ambivalent
13.9%
Positive/Warm
13.6%
Neutral/Functional
6.1%
Archetypes
21 detected
Ui/system
30.2%
Ambient Character
7.1%
Narrator
7.0%
Shieldbreaker
3.8%
Crusader
3.7%
Abomination
3.6%
Man-at-arms
3.2%
Arbalest
3.2%
Musketeer
3.2%
Antiquarian
3.1%
Houndmaster
3.1%
Grave Robber
3.1%
Plague Doctor
3.1%
Leper
3.1%
Highwayman
3.1%
Vestal
3.1%
Occultist
3.1%
Hellion
3.0%
Jester
3.0%
Bounty Hunter
2.8%
Flagellant
1.4%

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
10,498 / 10,744 lines
98%
Lex. Density
73.6 %
src
66.1%
Lex. Diversity
10.3 %
src
9.5%
MS
Malay
10,523 / 10,744 lines
98%
Lex. Density
73.6 %
src
66.1%
Lex. Diversity
8.9 %
src
9.5%
TL
Tagalog
10,424 / 10,744 lines
97%
Lex. Density
59.8 %
src
66.1%
Lex. Diversity
9.2 %
src
9.5%

* 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
31,702 Token Lines
Src Density
66.1%
Src Diversity
9.5%
Syntactic Error Report

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

81
Mismatch
81
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

Splitter (S0) 2026-09-22 14:08
Merger (S7) 2026-09-22 12:21
Tag Repair (S6) 2026-09-22 10:56
Corrector (S3) 2026-09-21 19:20
Translator (S2) 2026-09-21 19:11
Tagger (S1) 2026-09-21 17:13

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