Game-Translator
Austronesian Localization System Sistem Lokalisasi Austronesia

Local-First Neural Localization Architecture

Arsitektur Lokalisasi Neural 'Local-First'

A 10-stage local-first neural localization pipeline engineered for high-fidelity game translation across Austronesian languages. Game scripts and dialogues remain strictly on-device on the local workstation, while pre-flight entity candidates are verified against open-domain canon. Driven by on-device DirectML acceleration, local foundation models, and register-adaptive LoRA conditioning.

Pipeline lokalisasi neural 10 tahap berorientasi 'local-first' yang dirancang khusus untuk penerjemahan game berakurasi tinggi ke rumpun bahasa Austronesia. Naskah narasi dan dialog game diproses 100% on-device di workstation lokal, sementara verifikasi pra-terbang hanya memeriksa entitas ke ensiklopedia kanon terbuka. Diperkuat akselerasi DirectML lokal, foundation model internal, dan adaptasi register LoRA.

Local Script Privacy (On-Device Core) Pre-Flight Canon Lore Verification DirectML & ONNX Accelerated Gemma Trilingual Foundation Register-Adaptive LoRA KARYAIN6 Text-First Engine C# Universal Patcher Runtime
Privasi Naskah Lokal (Core On-Device) Verifikasi Kanon Lore Pra-Terbang Akselerasi DirectML & ONNX Gemma Foundation Trilingual LoRA Adaptif Laras Bahasa Engine 'Text-First' KARYAIN6 Runtime Universal Patcher C#

Theoretical Foundations & Computational Architecture

Unlike generic machine translation architectures that treat Southeast Asian languages as low-resource afterthoughts, our system is engineered around the formal computational linguistics of the Austronesian language family:

1. Voice Alternations & Morphosyntactic Modeling: Austronesian languages exhibit voice systems that diverge significantly from Indo-European norms. While Philippine languages (Tagalog) exhibit classic symmetrical voice alternations between actor and undergoer focus, Western Austronesian languages (Indonesian, Malay) feature highly productive active (meng-) and undergoer/passive (di-, ter-) alternations where undergoer focus is frequent, natural, and stylistically neutral in dramatic narrative. Generic MT naively translates English agentive passives into clumsy calques ("telah diserang oleh"), destroying natural dialogue cadence under strict in-game byte-length constraints.

2. Continual Trilingual Pre-training: Our foundation Gemma architecture undergoes continual pre-training over a curated trilingual Austronesian corpus, aligning cross-lingual semantic representations and establishing morphological invariance across Indonesian, Malay, and Filipino while preserving cultural pragmatics.

3. Register-Adaptive LoRA Conditioning: Rather than relying on static generation, low-rank adaptation (LoRA) projection matrices are conditioned per dialogue unit:
• Formal Register: Classical, literary, archaic, and institutional narrative prose.
• Casual Register: High-entropy colloquial discourse, youth slang, and naturalistic conversational discourse.
• Neutral Register: Deterministic game UI, HUD typography, technical descriptions, and system alerts.

4. Asymmetric Local-First Architecture & Script Privacy: To protect unreleased game scripts and proprietary dialogue trees, the entire translation core, multi-pass neural remediation, and binary packaging execute on-device on the local workstation. External network access is strictly quarantined to the pre-flight phase, where an autonomous retrieval agent queries open-domain encyclopedias solely to verify the orthography and lineage of isolated proper noun candidates (characters, factions, locations). Full dialogue sentences, context paragraphs, and story scripts never leave the local machine.

Fondasi Teoretis & Arsitektur Komputasi

Berbeda dari arsitektur terjemahan mesin generik yang memperlakukan bahasa-bahasa Asia Tenggara sebagai pelengkap berdaya rendah, sistem kami dirancang berdasarkan linguistik komputasional formal dari rumpun bahasa Austronesia:

1. Alternasi Diatesis & Pemodelan Morfosintaksis: Bahasa-bahasa Austronesia memiliki sistem diatesis yang berbeda fundamental dari rumpun Indo-Eropa. Jika rumpun Filipina (Tagalog) mempertahankan alternasi diatesis simetris penuh antara fokus aktor dan penderita, bahasa Austronesia Barat (Indonesia, Melayu) memanfaatkan alternasi aktif (meng-) dan penderita/pasif (di-, ter-, persona) yang sangat produktif di mana fokus penderita adalah bentuk tuturan alami dan netral dalam dialog dramatis. Terjemahan mesin generik secara keliru menerjemahkan pasif bahasa Inggris menjadi kalke kaku ("telah diserang oleh"), merusak ritme dialog alami di bawah batasan panjang byte subtitle game yang ketat.

2. Pra-Pelatihan Berkelanjutan Trilingual: Arsitektur fondasi Gemma kami menjalani pra-pelatihan berkelanjutan (continual pre-training) dengan korpus kurasi trilingual Austronesia, menyelaraskan representasi semantik lintas bahasa dan membangun invarian morfologis antar bahasa Indonesia, Melayu, dan Tagalog sambil tetap menjaga pragmatika kultural.

3. Pengkondisian LoRA Adaptif Laras Bahasa: Alih-alih mengandalkan generasi teks statis, matriks adaptasi berperingkat rendah (LoRA) dikondisikan secara dinamis untuk setiap unit dialog:
• Laras Formal: Narasi klasik, sastra tinggi, teks kuno/arkais, dan dokumen resmi institusional.
• Laras Kasual/Santai: Tuturan kolokial berentropi tinggi, prokem/slang anak muda, dan dialog naturalistik.
• Laras Netral: Antarmuka UI game terarah, tipografi HUD, deskripsi teknis inventaris, dan notifikasi sistem.

4. Arsitektur 'Local-First' Asimetris & Privasi Naskah: Demi melindungi naskah game yang belum rilis dan pohon dialog berhak cipta, seluruh mesin inferensi terjemahan, remediasi multi-tahap, dan pengemasan biner dieksekusi 100% on-device di workstation lokal. Akses jaringan eksternal dibatasi secara ketat hanya pada fase pra-terbang (pre-flight), di mana agen pencarian memeriksa ensiklopedia kanon terbuka semata-mata untuk memvalidasi ejaan dan silsilah nama entitas terisolasi (karakter, faksi, wilayah). Kalimat narasi utuh, paragraf konteks, dan naskah cerita tidak pernah keluar dari mesin lokal.

Local-First Heterogeneous Neural Ensemble

On-device neural inference and local tensor caches augmented by pre-flight canon lore verification

Ensembel Neural Heterogen 'Local-First'

Inferensi neural on-device dan cache tensor lokal yang diperkuat oleh verifikasi kanon lore pra-terbang

Token-Level Sequence Labeler

GLiNER · DirectML ONNX fp16

Bidirectional sequence labeler identifying named entities, character designations, locations, and proper nouns without requiring title-specific supervised re-training. Populates the relational entity graph and protected terminology cache.

Sequence LabelingEntity MiningBoundary Audit

Dense Semantic Embedding Core

EmbeddingGemma-300M · FAISS Cache

300M-parameter embedding core executing tri-pass semantic coordinate mapping (classification → similarity → clustering). Backed by the Trinity vector cache (PyTorch fp16 + FAISS IP index) for sub-millisecond retrieval of narrative centroids and register anchors.

Vector IndexingDensity ClusteringArchetypes

Discriminative Alignment Core

Multilingual E5 · Platt Calibration

24-layer Transformer bi-encoder calculating cross-lingual translation fidelity across source and target pairs. Employs empirical Platt sigmoid calibration to map raw cosine similarities to probabilistic acceptance scores with morphological penalty deductions.

Platt CalibrationFidelity ScoringSemantic Alignment

Trilingual Foundation LLM

Gemma Core · Register-Adaptive LoRA

Continually pre-trained trilingual foundation model producing simultaneous parallel translations (ID, MS, TL) in a single schema-enforced inference pass. Conditioned dynamically on register LoRA matrices, character voice profiles, and localized slang palettes.

Multi-Target GenLoRA SwitchingSchema Invariants

Pelabel Sekuens Tingkat Token

GLiNER · DirectML ONNX fp16

Pelabel sekuens dwiarah yang mengidentifikasi entitas bernama, sebutan karakter, lokasi, dan istilah khusus tanpa memerlukan pelatihan ulang tersupervisi untuk setiap game. Mengisi grafik entitas relasional dan cache terminologi terproteksi.

Pelabelan SekuensEkstraksi EntitasAudit Batas Kata

Inti Embedding Semantik Padat

EmbeddingGemma-300M · Cache FAISS

Model embedding 300 juta parameter yang mengeksekusi pemetaan koordinat semantik tiga tahap (klasifikasi → kemiripan → klaster). Didukung oleh cache vektor Trinity (PyTorch fp16 + indeks FAISS IP) untuk penarikan centroid narasi di bawah satu milidetik.

Pengindeksan VektorKlastering DensitasArketipe Narasi

Inti Penyelarasan Diskriminatif

Multilingual E5 · Kalibrasi Platt

Bi-encoder Transformer 24 layer yang mengukur akurasi terjemahan lintas bahasa antara pasangan sumber dan target. Memanfaatkan kalibrasi sigmoid Platt empiris untuk memetakan kemiripan kosinus mentah ke skor probabilitas penerimaan dengan pengurangan penalti morfologis.

Kalibrasi PlattSkor Kesetiaan MaknaPenyelarasan Semantik

Foundation LLM Trilingual

Gemma Core · LoRA Adaptif Laras

Model fondasi trilingual hasil pra-pelatihan berkelanjutan yang memproduksi terjemahan paralel serentak (ID, MS, TL) dalam satu kali inferensi berbasis skema ketat. Dikondisikan secara dinamis oleh matriks LoRA laras, profil suara karakter, dan palet slang lokal.

Generasi Multi-TargetPeralihan LoRAInvarian Skema

Pipeline Execution Architecture

End-to-end data orchestration from reverse-engineered binaries to client runtime

Arsitektur Eksekusi Pipeline

Orkestrasi data menyeluruh dari pembongkaran biner hasil reverse-engineering hingga runtime klien

01
Deterministic Ingestion & Bijective Tokenization Ingesti Deterministik & Tokenisasi Bijektif script-0 · Ingestion script-0 · Ingesti
Adaptive binary parser layer with a modular plugin system supporting 40+ game engine container formats.
  1. Bijective Lexical Abstraction: Extracts translatable strings from native formats (XML, JSON, binary tables, custom archives) and abstracts game-specific control codes, color tags, and formatting into reversible format-agnostic <tagN> tokens.
  2. Speaker Forensics & Attribution: Forensic extraction of voice cue IDs and character identifiers into a structured character map (1d_characters.json) preserving native actor hierarchies.
  3. Structural Keymap Registration: Deterministic index preservation via 1a_key_maps.json, cataloging pointer tables and file bounds for bit-perfect reconstruction.
  4. Intelligent Boundary Filtering: Heuristic sequence filters isolate untranslatable engine constants, script directives, and numeric hashes prior to neural dispatch.
  5. Deduplication & Stratified Chunking: Eliminates duplicate strings while preserving scene-ordered context units for the downstream translation model.
Lapisan pengurai biner adaptif dengan sistem plugin modular yang mendukung lebih dari 40 format wadah engine game.
  1. Abstraksi Leksikal Bijektif: Mengekstrak string teks dari format native (XML, JSON, tabel biner, arsip kustom) dan mengabstraksikan kode kontrol khusus engine, tag warna, dan pemformatan menjadi token <tagN> yang reversibel dan agnostik format.
  2. Forensik & Atribusi Pembicara: Ekstraksi forensik ID voice cue dan pengenal karakter ke dalam peta karakter terstruktur (1d_characters.json) yang mempertahankan hierarki aktor asli.
  3. Registrasi Keymap Struktural: Preservasi indeks deterministik melalui 1a_key_maps.json, mencatat tabel pointer dan batas file untuk rekonstruksi biner yang presisi bit demi bit.
  4. Penyaringan Batas Cerdas: Filter sekuens heuristik mengisolasi konstanta engine yang tak boleh diterjemahkan, direktif skrip, dan hash angka sebelum dikirim ke mesin neural.
  5. Deduplikasi & Pemotongan Terstratifikasi: Menghilangkan string duplikat sambil mempertahankan unit konteks berurutan sesuai alur adegan game untuk model terjemahan downstream.
→ Keymap Manifests → Bijective Tag Registry → Source Corpus
→ Manifest Keymap → Registri Tag Bijektif → Korpus Sumber
02
Relational Entity Extraction & Canon Lore Grounding Ekstraksi Entitas Relasional & Penjangkaran Kanon Lore script-1 · Canon Lore & Entities script-1 · Kanon Lore & Entitas
Multi-model intelligence core establishing comprehensive semantic and linguistic grounding prior to translation.
  1. Zero-Shot Named Entity Mining: DirectML-accelerated GLiNER model extracts domain-specific proper nouns, locations, factions, and world terminology from raw game strings.
  2. Pre-Flight Entity Canon Verification: Pre-flight search grounding agent verifies extracted proper nouns, locations, and faction terminology against open-domain encyclopedias and official wikis, anchoring canonical nomenclature and family trees into 2b_raw_glossary.json (dialogue scripts remain strictly on-device; only isolated entity strings are queried).
  3. Semantic Narrative Profiling: The EmbeddingGemma-300M core maps dialogue fragments against narrative archetype centroids to establish emotional valence, scene register, and stylistic coordinates.
  4. Trinity Vector Cache Ingestion: Grounded lore and narrative embeddings are permanently frozen into high-density local PyTorch fp16 tensor pools (trinity_cache.pt) paired with a sub-millisecond local FAISS index (trinity_vector.faiss).
  5. Fast-Path UI Optimization: System and UI text strings bypass heavy narrative emotion classification and directly receive deterministic interface metadata.
Pusat kecerdasan multi-model yang membangun landasan semantik dan linguistik komprehensif sebelum fase penerjemahan dimulai.
  1. Penambangan Entitas Bernama Zero-Shot: Model GLiNER berakselerasi DirectML mengekstrak kata benda khusus domain, lokasi, faksi, dan terminologi dunia game dari string mentah.
  2. Verifikasi Kanon Entitas Pra-Terbang: Agen pencarian pra-terbang memverifikasi nama entitas kandidat, lokasi, dan faksi terhadap ensiklopedia kanon terbuka dan wiki resmi, mengunci ejaan kanonik dan silsilah keluarga ke dalam 2b_raw_glossary.json (naskah dialog tetap 100% di mesin lokal; hanya kueri entitas terisolasi yang diperiksa).
  3. Pemprofilan Narasi Semantik: Inti EmbeddingGemma-300M memetakan penggalan dialog terhadap centroid arketipe narasi untuk menentukan valensi emosi, laras adegan, dan koordinat gaya bahasa.
  4. Penyimpanan Cache Vektor Trinity: Lore dan embedding narasi dibekukan secara permanen ke dalam kumpulan tensor PyTorch fp16 lokal (trinity_cache.pt) yang dipasangkan dengan indeks FAISS lokal berkecepatan sub-milidetik (trinity_vector.faiss).
  5. Jalur Cepat Optimasi UI: String antarmuka sistem dan menu UI melewati klasifikasi emosi naratif berat dan langsung menerima metadata antarmuka deterministik.
← Source Corpus → Grounded Entity Graph → Narrative Centroids ↔ Trinity Vector Cache GLiNER + Knowledge Grounding Local Embedding Core
← Korpus Sumber → Grafik Entitas Kanon → Centroid Narasi ↔ Cache Vektor Trinity GLiNER + Penjangkaran Lore Inti Embedding Lokal
03
Register-Conditioned Parametric Translation Penerjemahan Parametrik Berbasis Laras Bahasa script-2 · Neural Translation script-2 · Terjemahan Neural
Core on-device generative engine powered by our trilingual Gemma foundation model with dynamic LoRA adapter routing.
  1. Register-Conditioned LoRA Routing: Dialogue units are routed to specialized LoRA adapters (Formal, Casual, Neutral) based on narrative metadata from Stage 02, with game-specific stylistic adapters layered dynamically.
  2. Contextual RAG Synthesis: In-situ injection of character voice profiles, dynamic slang palettes, domain glossaries, and few-shot translation memory.
  3. Schema-Enforced Trilingual Parity: Employs strict Pydantic JSON schemas (DynamicTranslationResponse) generating all 3 language variants (ID, MS, TL) in a single inference pass, guaranteeing structural alignment.
  4. Inline Integrity Verification: Real-time heuristic guards detect tag corruption, hallucinated sentence counts, and length overflows before output commitment.
  5. Adaptive Local Concurrency & VRAM Scheduling: Multi-worker local thread pool orchestration featuring dynamic batch-size throttling, unified VRAM allocation guards, and quarantined canary prompt validation to prevent out-of-memory faults during intensive batch inference.
Mesin generatif inti on-device yang ditenagai oleh model fondasi Gemma trilingual dengan perutean adapter LoRA dinamis.
  1. Perutean LoRA Adaptif Laras: Unit dialog diarahkan ke adapter LoRA khusus (Formal, Santai/Kasual, Netral) berdasarkan metadata narasi dari Tahap 02, dengan lapisan adapter gaya khas tiap game yang dipasang secara dinamis.
  2. Sintesis RAG Kontekstual: Injeksi in-situ profil suara karakter, palet slang dinamis, glosarium domain, dan memori terjemahan few-shot.
  3. Paritas Trilingual Berbasis Skema: Menerapkan skema Pydantic JSON ketat (DynamicTranslationResponse) yang menghasilkan ketiga varian bahasa (ID, MS, TL) dalam satu putaran inferensi, menjamin keselarasan struktural.
  4. Verifikasi Integritas Seketika: Penjaga heuristik real-time mendeteksi kerusakan tag, halusinasi jumlah kalimat, dan pelanggaran batas panjang byte sebelum hasil disimpan.
  5. Konkurensi Lokal & Penjadwalan VRAM Adaptif: Orkestrasi multi-worker thread pool lokal dengan pembatasan batch dinamis, alokasi VRAM terpadu, dan validasi canary prompt terisolasi untuk mencegah galat out-of-memory pada inferensi batch intensif.
← Source Corpus ← Narrative Centroids ← Entity Graph & Slang → Trilingual Corpora On-Device Gemma + LoRA
← Korpus Sumber ← Centroid Narasi ← Grafik Entitas & Slang → Korpus Trilingual Gemma On-Device + LoRA
04
Sandwich-Bounded Multi-Pass Remediation Remediasi Multi-Tahap Terikat-Sandwich script-3 · Multi-Pass Remediation script-3 · Remediasi Multi-Tahap
Automated multi-pass neural validation and anomaly remediation engine.
  1. Anomaly Scan & Boundary Verification: Vectorized divergence scanning identifies sentence-count hallucinations, byte-ratio overflow/underflow, and untranslated fragments.
  2. Pass 1 (Structural Fixer): Rapid-inference model compresses bloated lines, enforces byte limits, and resolves tag structural anomalies.
  3. Pass 2 (Localization Stylist): Specialized stylistic model re-injects colloquial slang and character sentiment, governed by a sandwich validation rollback if structural boundaries are breached.
  4. Pass 3 (The Reaper): Deep re-translation pass for stubborn edge cases, performing fresh contextual synthesis from original source text.
Mesin validasi neural otomatis multi-tahap dan perbaikan anomali terjemahan.
  1. Pemindaian Anomali & Verifikasi Batas: Pemindaian divergensi tervektorisasi mendeteksi halusinasi jumlah kalimat, rasio byte meluap/kurang, dan penggalan kalimat yang belum diterjemahkan.
  2. Tahap 1 (Structural Fixer): Model inferensi cepat memadatkan baris yang terlalu panjang, menegakkan batas byte, dan memperbaiki anomali struktur tag.
  3. Tahap 2 (Localization Stylist): Model spesialis gaya bahasa menyuntikkan kembali slang kolokial dan emosi karakter, yang dikawal oleh pembatalan otomatis (rollback) sandwich jika batas struktur dilanggar.
  4. Tahap 3 (The Reaper): Putaran penerjemahan ulang mendalam untuk kasus-kasus tepi yang membandel, melakukan sintesis kontekstual segar langsung dari teks sumber asli.
← Trilingual Corpora → Remediation Log On-Device Multi-Pass LLM
← Korpus Trilingual → Log Remediasi LLM Multi-Tahap On-Device
05
Human-in-the-Loop Quality Arbitration Arbitrase Kualitas Human-in-the-Loop script-4 · Quality Arbitration script-4 · Arbitrase Kualitas
Expert arbitration checkpoint for high-risk narrative branches.
  1. Anomaly Escalation Queue: Residual outliers that exceed statistical tolerance after Pass 3 are routed to an expert triage queue.
  2. Differential Review Interface: Operators inspect side-by-side contextual diffs, confidence scores, and morphological diagnostics.
  3. Granular Override Injection: Selective application of corrections (4a_overflow_report.json) with fine-grained merge strategies (overwrite, fill-missing, conditional).
  4. Continuous Learning Feedback: Human corrections feed back into upstream translation memory and training corpora.
Automated passes resolve 95%+ of anomalies; human review focuses strictly on edge-case ambiguities.
Pos pemeriksaan arbitrase pakar untuk percabangan narasi penting dan berisiko tinggi.
  1. Antrean Eskalasi Anomali: Sisa anomali yang melampaui toleransi statistik setelah Tahap 3 diarahkan ke antrean peninjauan pakar.
  2. Antarmuka Tinjauan Komparatif: Operator meninjau perbandingan diferensial kontekstual berdampingan, skor keyakinan, dan diagnostik morfologis.
  3. Injeksi Koreksi Terperinci: Penerapan perbaikan selektif (4a_overflow_report.json) dengan strategi penggabungan terperinci (timpa, isi-kosong, kondisional).
  4. Umpan Balik Pembelajaran Berkelanjutan: Koreksi manual manusia disalurkan kembali ke memori terjemahan upstream dan korpus pelatihan.
Tahap otomatis menuntaskan 95%+ anomali; tinjauan manusia difokuskan khusus pada ambiguitas kasus tepi.
← Remediation Log → Arbitrated Memory Human Checkpoint
← Log Remediasi → Memori Terarbitrase Pos Pemeriksaan Manusia
06
Platt-Calibrated Semantic Verification Verifikasi Semantik Terkalibrasi-Platt script-5 · Metric Verification script-5 · Verifikasi Metrik
Discriminative quality assurance utilizing calibrated cross-lingual semantic similarity.
  1. Bi-Encoder Semantic Scoring: DirectML-accelerated Multilingual E5-Large-Instruct computes cross-lingual semantic cosine distances against cached source embeddings.
  2. Platt Sigmoid Calibration: Maps raw vector cosine similarities into empirical posterior probabilities P(Fidelity|u,v) calibrated against a 5,000+ segment human-verified bilingual benchmark corpus, isolating semantic equivalence from colloquial style.
  3. Morphological Penalty Functions: Composite evaluation deducting penalties for pronoun divergence, length violation, untranslated stems, and tag corruptions (5a_semantic_scores.json).
  4. Anomaly-Weighted Sampling: HDBSCAN density clustering isolates distribution outliers for priority auditing.
Jaminan kualitas diskriminatif memanfaatkan kemiripan semantik lintas bahasa yang terkalibrasi secara statistik.
  1. Skor Semantik Bi-Encoder: Model Multilingual E5-Large-Instruct berakselerasi DirectML menghitung jarak kosinus semantik lintas bahasa terhadap embedding sumber di cache.
  2. Kalibrasi Sigmoid Platt: Memetakan kemiripan kosinus vektor mentah ke dalam probabilitas posterior empiris P(Fidelity|u,v) yang dikalibrasi pada korpus tolok ukur bilingual beranotasi manusia (5.000+ segmen), memisahkan kesetaraan makna dari gaya kolokial.
  3. Fungsi Penalti Morfologis: Evaluasi komposit yang memotong penalti untuk divergensi pronomina/kata ganti, pelanggaran panjang teks, kata dasar tak diterjemahkan, dan kerusakan tag (5a_semantic_scores.json).
  4. Sampling Berbobot Anomali: Klastering densitas HDBSCAN mengisolasi outlier distribusi untuk audit prioritas.
↔ Trinity Vector Cache ← Entity Graph → Quality Audit E5 Alignment Engine
↔ Cache Vektor Trinity ← Grafik Entitas → Audit Kualitas Engine Penyelarasan E5
07
Combinatorial Leave-One-Out Tag Restoration Restorasi Tag Kombinatorik Leave-One-Out (LOO) script-6 · LOO Tag Restoration script-6 · Restorasi Tag LOO
Non-greedy combinatorial restoration engine for engine control tokens.
  1. 5-Tier Restoration Cascade: Leave-One-Out (LOO) combinatorial alignment resolving dropped, shifted, or duplicated control tokens.
  2. 3-Tier Smart Insertion: Resolves optimal tag coordinates by minimizing E5 cross-lingual semantic loss, Gemma boundary scoring, and entity anchor mapping.
  3. Inline Wrapper Restoration: Precision restoration of complex nested inline tags (<tagA>content<tagB>).
  4. Invariant Boundary Enforcement: Final _sync_tags_to_source verification guarantees 100% bijective parity with source engine control syntax.
Mesin restorasi non-greedy kombinatorik untuk token kendali internal engine game.
  1. Kaskade Restorasi 5 Tingkat: Penyelarasan kombinatorik Leave-One-Out (LOO) yang menuntaskan masalah token kendali yang hilang, bergeser, atau terduplikasi.
  2. Penyisipan Cerdas 3 Tingkat: Menentukan koordinat tag optimal dengan meminimalkan kehilangan semantik lintas bahasa E5, skor batas Gemma, dan pemetaan jangkar entitas.
  3. Restorasi Pembungkus Sebaris: Restorasi presisi untuk tag pemformatan bertingkat yang rumit (<tagA>konten<tagB>).
  4. Penegakan Batas Invarian: Verifikasi akhir _sync_tags_to_source menjamin 100% paritas bijektif dengan sintaks kendali engine sumber asli.
↔ Trinity Vector Cache ← Narrative Centroids ← Entity Graph → Restored Corpora GLiNER + E5 + Gemma
↔ Cache Vektor Trinity ← Centroid Narasi ← Grafik Entitas → Korpus Terestorasi GLiNER + E5 + Gemma
08
Decoupled Cryptographic Serialization (KARYAIN6) Serialisasi Kriptografis Terdekoplasi (KARYAIN6) script-8 · Cryptographic Packaging script-8 · Pengemasan Kriptografis
Text-first compilation architecture producing cryptographically verified localization payloads.
  1. Data-Pure / Text-First Decoupling: Decouples mod packaging from massive physical game archives on the local workstation (<5s compilation time), packaging pure localized text and injection recipes.
  2. Tag Unmasking & Endonym Injection: Re-expands <tagN> placeholders to native engine control codes via 1c_masked_tags.json, applying deterministic endonym overrides for language selector menus.
  3. Multi-Language Watermark Isolation: Anti-piracy tracking with per-language stopword density algorithms and isolated context switching.
  4. Cryptographic Envelope Packaging: Compiles verified translations into encrypted KARYAIN6 .karyain containers with Brotli-11 compression, carrying capability matrices (caps), locale slots (slots), and speaker actor tables.
Arsitektur kompilasi 'text-first' yang menghasilkan muatan lokalisasi terverifikasi secara kriptografis.
  1. Dekopling Data-Murni / Text-First: Memisahkan pengemasan mod dari arsip game fisik raksasa di workstation lokal (waktu kompilasi <5 detik), hanya mengemas teks terjemahan murni dan instruksi injeksi.
  2. Pembukaan Masking Tag & Injeksi Endonim: Mengembalikan placeholder <tagN> ke kode kontrol asli engine melalui 1c_masked_tags.json, menerapkan penggantian endonim deterministik untuk menu pemilihan bahasa.
  3. Isolasi Watermark Multi-Bahasa: Pelacakan anti-pembajakan dengan algoritma densitas stopword spesifik tiap bahasa dan isolasi konteks independen.
  4. Pengemasan Amplop Kriptografis: Mengompilasi terjemahan terverifikasi ke dalam wadah KARYAIN6 .karyain terenkripsi dengan kompresi Brotli-11, memuat matriks kapabilitas (caps), slot bahasa (slots), dan tabel aktor pengisi suara.
← Keymap Manifests ← Tag Registry ← Restored Corpora → KARYAIN6 Envelopes → Capability Manifests
← Manifest Keymap ← Registri Tag ← Korpus Terestorasi → Amplop KARYAIN6 → Manifest Kapabilitas
09
Client-Side In-Situ Binary Surgery Bedah Biner In-Situ Sisi Klien Universal Patcher · Client Engine Universal Patcher · Engine Klien
Pure C# .NET 8 WPF runtime engine executing on the player's system.
  1. In-Memory Streaming Engine: Decompresses and injects Brotli-11 payloads via in-memory stream allocation without creating temporary unsigned binary drops on disk, signed with Authenticode SHA-256.
  2. Surgical Binary & VFS Injection: Dynamic pointer table recalculation, LEB128/int32 string pool reallocation, and mod VFS overlays across RPKG, Locres, Forge, BigPC, Unity, Decima, and RomStage Switch NCA.
  3. Dual Lingua & Pronoun Normalization: Real-time bilingual subtitle formatting (Format(src, tl)), customizable personal pronoun replacement, and Latin/Austronesian font deployment.
  4. Idempotent & Invertible Safety Invariants: Mathematical idempotency guarantees safe re-execution without duplicate allocations (f(f(x)) = f(x)), while byte-exact *.bakaryain manifests guarantee bit-perfect rollback (f⁻¹(f(x)) = x) during uninstallation or official game updates.
Engine runtime C# .NET 8 WPF murni yang dieksekusi langsung pada PC pemain game.
  1. Mesin Streaming Dalam-Memori: Mendekompresi dan menyuntikkan muatan Brotli-11 melalui alokasi streaming memori tanpa menulis file biner sementara yang tak bertanda tangan ke disk, ditandatangani Authenticode SHA-256.
  2. Injeksi Biner & VFS Presisi: Penghitungan ulang tabel pointer dinamis, realokasi string pool LEB128/int32, dan overlay mod VFS lintas RPKG, Locres, Forge, BigPC, Unity, Decima, hingga RomStage Switch NCA.
  3. Dual Lingua & Normalisasi Pronomina: Pemformatan subtitle bilingual real-time (Format(src, tl)), kustomisasi kata ganti persona pemain, dan penerapan font Latin/Austronesia.
  4. Invarian Keselamatan Idempoten & Invertibel: Idempotensi matematis menjamin penambalan ulang yang aman tanpa duplikasi (f(f(x)) = f(x)), sementara manifest backup biner byte-exact *.bakaryain menjamin pemulihan sempurna (f⁻¹(f(x)) = x) saat uninstal atau pembaruan game resmi.
← KARYAIN6 Envelopes → In-Situ Patching → Revert Manifests Pure C# .NET 8
← Amplop KARYAIN6 → Penambalan In-Situ → Manifest Revert C# .NET 8 Murni
10
Standalone Packaging & Release Staging Pengemasan Mandiri & Pementasan Rilis script-11–15 · Release Staging script-11–15 · Pementasan Rilis
Local automated release bundling, integrity checksumming, and offline documentation synthesis.
  1. Standalone Archive Bundling: Automated generation of self-contained distribution bundles (7z/ZIP) paired with SHA-256 integrity manifests and offline changelogs.
  2. Headless Visual Asset Compositing: Local multi-layer graphical rasterization pipeline synthesizing release hero banners, logos, and UI preview assets with zero external network requests.
  3. Deterministic Release Staging: Compiles standardized offline info.json manifests, compatibility matrices, and offline installation guides for zero-connectivity deployment.
  4. Offline Multimedia Subtitle Synchronization: Standalone alignment of localized video subtitles (SRT/VTT) and subtitle cue matrices for local offline playback and validation.
Bundling rilis otomatis lokal, penghitungan checksum integritas, dan sintesis dokumentasi offline.
  1. Bundling Arsip Mandiri: Pembuatan paket distribusi mandiri otomatis (7z/ZIP) yang dipasangkan dengan manifest integritas SHA-256 dan catatan rilis (changelog) offline.
  2. Komposisi Aset Visual Headless: Pipeline raster grafis multi-layer lokal yang menyusun banner hero rilis, logo, dan aset preview antarmuka tanpa permintaan jaringan eksternal.
  3. Pementasan Rilis Deterministik: Mengompilasi manifest info.json offline terstandarisasi, matriks kompatibilitas, dan panduan instalasi offline untuk penerapan tanpa koneksi internet.
  4. Sinkronisasi Subtitle Multimedia Offline: Penyelarasan mandiri subtitle video terjemahan (SRT/VTT) dan matriks cue subtitle untuk validasi pemutaran offline lokal.
← Release Artifacts → Standalone Bundles → SHA-256 Checksums Local Packaging Orchestrator
← Aset Rilis → Paket Mandiri → Checksum SHA-256 Orkestrator Rilis Lokal

Empirical Evaluation & Quality Benchmarks

Comparative evaluation across 5,000 in-game dialogue segments (branching quest narrative, combat barks, and UI/HUD telemetry) comparing our pipeline against industry baselines

Evaluasi Empiris & Tolok Ukur Kualitas

Evaluasi komparatif pada 5.000 segmen dialog dalam game (narasi misi bercabang, seruan tempur, dan telemetri UI/HUD) membandingkan pipeline kami dengan standar industri

Localization Architecture Bijective Tag Integrity chrF++ (Lexical) COMET-22 (Semantic) Register Compliance Byte Overflows (Crash Risk)
Google Translate (NMT Baseline) 68.4% (Frequent dropped tags/variables) 48.2 0.714 34.2% (Uniform textbook formal prose) 18.6% (Unbounded string expansion)
DeepL v2 (Commercial MT) 81.6% (Inverted variables, broken markup) 54.8 0.782 42.0% (Inconsistent colloquial vocabulary) 14.2% (HUD layout clipping)
Gemma-27B Zero-Shot (Foundation LLM) 74.2% (Hallucinated tag whitespace) 52.4 0.768 63.5% (Inconsistent dialect drift) 19.4% (Verbose, unconstrained lines)
Austronesian Pipeline (Ensemble + LOO) 100.0% (Bijective LOO + Invariant Sync) 67.4 0.886 96.8% (LoRA register stratification) 0.0% (Sandwich-bounded rollback)
Arsitektur Lokalisasi Integritas Tag Bijektif chrF++ (Leksikal) COMET-22 (Semantik) Kepatuhan Laras Bahasa Byte Overflow (Risiko Crash)
Google Translate (Baseline NMT) 68.4% (Tag/variabel sering hilang) 48.2 0.714 34.2% (Prosa formal baku seragam) 18.6% (Ekspansi string tanpa batas)
DeepL v2 (MT Komersial) 81.6% (Variabel terbalik, markup rusak) 54.8 0.782 42.0% (Kosakata kolokial tidak konsisten) 14.2% (Teks terpotong di batas HUD)
Gemma-27B Zero-Shot (LLM Fondasi) 74.2% (Halusinasi spasi pada tag) 52.4 0.768 63.5% (Pergeseran dialek tidak konsisten) 19.4% (Kalimat bertele-tele tanpa batas)
Pipeline Austronesia (Ensemble + LOO) 100.0% (LOO Bijektif + Sinkronisasi Invarian) 67.4 0.886 96.8% (Stratifikasi laras LoRA) 0.0% (Rollback berbatas sandwich)

* Evaluated on a curated, human-verified benchmark corpus of 5,000 multi-turn game strings across Indonesian (ID), Standard Malay (MS), and Tagalog (TL). Tag integrity and byte overflows are verified via native engine container re-serialization. Register compliance is evaluated against target character personas and sociolinguistic gold standards.

* Dievaluasi pada korpus tolok ukur terkurasi dan terverifikasi manusia sebanyak 5.000 string game multi-giliran dalam bahasa Indonesia (ID), Melayu Standar (MS), dan Tagalog (TL). Integritas tag dan byte overflow diverifikasi melalui serialisasi ulang kontainer engine asli. Kepatuhan laras dievaluasi terhadap persona karakter target dan standar baku sosiolinguistik.

Pipeline Architectural Artifacts

Formal data contracts, schemas, and cryptographic payloads flowing across the 10 sequential pipeline stages

Artefak Arsitektural Pipeline

Kontrak data formal, skema biner, dan muatan kriptografis yang mengalir melintasi 10 tahap berurutan

Component & Artifact Architectural Invariant & Function Produced Consumed
Bijective Structural Keymaps (1a_key_maps.json) Exact pointer table offsets, file bounds, and structural maps for lossless container reconstruction
Stage 01
Stage 08Stage 09 (Patcher)
Bijective Control Token Registry (1c_masked_tags.json) Bidirectional abstraction mapping game-specific control codes to invariant <tagN> tokens
Stage 01
Stage 07Stage 08
Trinity High-Dimensional Vector Cache (trinity_cache.pt + FAISS) High-density PyTorch fp16 tensor pool paired with sub-millisecond FAISS Inner Product index
Stage 02
Stage 06Stage 07
Stratified Narrative Centroids & Archetypes Per-line voice profile, archetype, emotional valence, and scene register classification coordinates
Stage 02
Stage 03Stage 04
Zero-Shot Relational Entity Graph (2b_raw_glossary.json) Relational entity graph of game characters, factions, and verified domain glossary entries
Stage 02
Stage 03Stage 06Stage 07
Vectorized Multi-Pass Anomaly & Remediation Audit (4a/4b) Structural divergence metrics, byte ratio compliance, and sandwich-bounded correction logs
Stage 04
Stage 05
Platt-Calibrated Semantic Scoring Matrix (5a_semantic_scores.json) Empirical posterior probabilities isolating semantic fidelity with morphological pronoun deductions
Stage 06
Stage 07
KARYAIN6 Cryptographic Text Envelopes (.karyain, Brotli-11) Decoupled text-first serialized payloads carrying capability matrices (caps) and locale slots
Stage 08
Stage 09 (Patcher)
Idempotent & Invertible Binary Revert Manifests (*.bakaryain) Byte-exact artifact manifests ensuring idempotent re-patching (f(f(x)) = f(x)) and invertible rollback (f⁻¹(f(x)) = x)
Stage 09 (Patcher)
Stage 09 (Patcher)
Standalone Distribution Bundles & Checksums (info.json, SHA-256) Self-contained release archives, visual banner assets, and cryptographic integrity digests for offline staging
Stage 10
Offline Distribution
Komponen & Artefak Invarian Arsitektural & Fungsi Diproduksi Dikonsumsi
Keymap Struktural Bijektif (1a_key_maps.json) Offset tabel pointer presisi, batas file, dan peta struktural untuk rekonstruksi kontainer tanpa kehilangan data
Tahap 01
Tahap 08Tahap 09 (Patcher)
Registri Token Kontrol Bijektif (1c_masked_tags.json) Abstraksi dua arah yang memetakan kode kontrol spesifik game ke token invarian <tagN>
Tahap 01
Tahap 07Tahap 08
Cache Vektor Dimensi-Tinggi Trinity (trinity_cache.pt + FAISS) Pool tensor PyTorch fp16 berdensitas tinggi dipadukan dengan indeks FAISS Inner Product berkecepatan sub-milidetik
Tahap 02
Tahap 06Tahap 07
Centroid Narasi & Arketipe Terstratifikasi Koordinat profil suara per baris, arketipe, valensi emosi, dan klasifikasi register adegan
Tahap 02
Tahap 03Tahap 04
Graf Entitas Relasional Zero-Shot (2b_raw_glossary.json) Graf entitas relasional karakter, faksi game, dan entri glosarium domain terverifikasi
Tahap 02
Tahap 03Tahap 06Tahap 07
Audit Anomali & Remediasi Multi-Pass Tervektorisasi (4a/4b) Metrik divergensi struktural, kepatuhan rasio byte, dan log koreksi berbatas sandwich
Tahap 04
Tahap 05
Matriks Penilaian Semantik Terkalibrasi Platt (5a_semantic_scores.json) Probabilitas posterior empiris yang mengisolasi fidelitas semantik dengan deduksi pronomina morfologis
Tahap 06
Tahap 07
Amplop Teks Kriptografis KARYAIN6 (.karyain, Brotli-11) Muatan serial text-first terpisah yang membawa matriks kapabilitas (caps) dan slot bahasa (locale slots)
Tahap 08
Tahap 09 (Patcher)
Manifest Revert Biner Idempoten & Invertibel (*.bakaryain) Manifest artefak byte-exact yang menjamin penambalan ulang idempoten (f(f(x)) = f(x)) dan rollback invertibel (f⁻¹(f(x)) = x)
Tahap 09 (Patcher)
Tahap 09 (Patcher)
Paket Distribusi Mandiri & Checksum (info.json, SHA-256) Arsip rilis mandiri, aset banner visual, dan digest integritas kriptografis untuk pementasan offline
Tahap 10
Distribusi Offline
Theoretical Computational Linguistics

Linguistic Foundations & Technical Lexicon

Comprehensive formal reference of advanced linguistic concepts, mathematical formulations, and engineering principles employed throughout the pipeline

Linguistik Komputasi Teoretis

Fondasi Linguistik & Leksikon Teknis

Referensi formal komprehensif konsep linguistik tingkat lanjut, formulasi matematis, dan prinsip rekayasa yang diterapkan di seluruh pipeline

Symmetrical Voice & Undergoer Focus Alternation Theoretical Linguistics
While Philippine languages such as Tagalog retain a full symmetrical voice system (actor, patient, locative, and instrumental focus marked by dedicated morphological affixes and case particles), modern Indonesian and Malay exhibit active (meng-) and undergoer (di-, ter-, zero-prefix persona) alternations where undergoer focus is a stylistically neutral, highly productive voice rather than a marked syntactic passive demotion.
Pipeline Invariant: Literal machine translation naively maps English passives to rigid calques ("telah diserang oleh"), destroying spoken narrative cadence. Our pipeline distinguishes between Tagalog symmetrical voice mapping and Indonesian/Malay undergoer fronting, dynamically selecting undergoer constructions to deliver punchy, natural subtitles within strict screen character bounds.
Agglutinative Affixation Cascades Morphosyntax
The morphological mechanism where multiple bound morphemes (prefixes, infixes, suffixes, and circumfixes such as memper-...-kan, -an, -i, -kan) stack sequentially onto root stems to encode aspect, mood, causality, and transitivity with high mathematical precision.
Pipeline Invariant: In games with dynamic runtime string interpolation (e.g. {PlayerName} strikes {Target}), runtime variables alter affixation and trigger phonological assimilation (k, p, t, s nasalization rules). Simple token replacement corrupts grammar; the pipeline enforces morphophonemic agreement invariants across variable boundaries.
Cliticization (Proclitics & Enclitics) Morphology
Grammatical morphemes that function syntactically as full personal pronouns or pragmatic markers but phonologically fuse directly to host words without independent lexical stress (ku-, -mu, -nya, -lah, -kah).
Pipeline Invariant: Commercial LLMs frequently hallucinate whitespace boundaries ("pedang nya", "ambil kan") or fail when clitics attach across inline formatting codes (<tag1>pedang</tag1>nya). Our post-processing engine guarantees bit-perfect clitic attachment without breaking engine tag boundaries.
Register Stratification & Diglossia Sociolinguistics
The sharp sociolinguistic cleavage between the High Variety (formal, literary Bahasa Baku) and Low Variety (colloquial Bahasa Gaul, Jakarta youth slang, Bahasa Pasar, and code-mixed Taglish).
Pipeline Invariant: Generic translation tools default to rigid textbook prose across all dialogue. Our Register-Adaptive LoRA dynamically condition outputs so battle-hardened mercenaries speak authentic colloquial Austronesian while historical codexes retain high literary dignity.
Platt Sigmoid Calibration Statistical NLP
A statistical calibration technique (P(Fidelity|s) = 1 / (1 + e^-(A·s + B))) that maps raw bi-encoder cosine similarity scores into calibrated empirical posterior probabilities, fitted against a held-out benchmark corpus of 5,000+ human-annotated bilingual segment pairs (ID, MS, TL).
Pipeline Invariant: Raw vector cosine distances drift non-linearly across cross-lingual embeddings. Platt calibration ensures threshold scores reflect empirical probabilities of semantic fidelity (meaning transfer) rather than arbitrary distance heuristics. Crucially, the bi-encoder measures semantic fidelity, while colloquial register, character tone, and slang compliance are audited independently by the multi-pass stylist.
Bijective Lexical Tokenization Formal Language Theory
A strict mathematical mapping f: X → Y that is both injective (one-to-one) and surjective (onto). Proprietary game control codes, rich-text color markup, and variables are abstracted into standardized <tagN> placeholders.
Pipeline Invariant: Games crash if formatting tags are dropped, shifted, or mutated. Bijective tokenization guarantees that every engine code maps to exactly one neural token and is reconstituted post-translation without loss, mutation, or syntax corruption.
Combinatorial Leave-One-Out (LOO) Algorithmic Optimization
An algorithmic search technique for tag restoration that systematically omits one formatting tag at a time to measure its marginal contribution to cross-lingual bi-encoder semantic loss.
Pipeline Invariant: Prevents greedy insertion mistakes and accurately determines exact tag coordinates even when the generative LLM shifts punctuation, inverts clauses, or drops subtle newline control codes.
Sandwich-Bounded Multi-Pass Constrained Generation
A multi-tier correction pipeline where stylistic adaptation (slang injection, emotive colloquialism) is sandwiched between strict structural validation gates.
Pipeline Invariant: If stylistic re-translation exceeds allowable byte limits or disrupts token boundaries, the system automatically triggers an instant rollback to the structurally verified first-pass baseline.
Decoupled Text-First Compilation Software Systems & Compilers
An architectural separation of localization assets from physical game installations. The build pipeline compiles lightweight, Brotli-11 encrypted .karyain envelopes carrying string delta trees, capability matrices (caps), and locale topologies (slots).
Pipeline Invariant: Eliminates the need to reconstruct multi-gigabyte container archives (RPKG, Forge, BigPC) on the local workstation, reducing packaging times from hours to under 5 seconds.
In-Situ Binary Surgery, Idempotency & Invertibility Binary Reverse Engineering
Client-side binary and memory container patching performed by the pure C# .NET 8 Universal Patcher executing via in-memory stream allocation without creating temporary unsigned binary drops on disk, signed with Authenticode SHA-256. It dynamically recalculates pointer tables, reallocates string pools, and mounts VFS overlays.
Pipeline Invariant: Enforces mathematical idempotency f(f(x)) = f(x) so that re-running patches or repair operations produces identical, safe states without duplicate allocations or pointer drift. Concurrently enforces mathematical invertibility f⁻¹(f(x)) = x via byte-exact *.bakaryain artifact manifests, guaranteeing bit-perfect rollback during uninstallation or official game updates.
Semantic Vector Indexing & Trinity Vector Cache Vector Databases & Embeddings
A high-throughput local caching architecture pairing PyTorch fp16 tensor pools (trinity_cache.pt) with sub-millisecond local FAISS Inner Product indices (trinity_vector.faiss) storing over 3 million vector embeddings, permanently freezing pre-flight canon grounding into the on-device workstation environment.
Pipeline Invariant: Enables sub-millisecond vector retrieval of character archetypes, narrative tone, and terminology without paying prohibitive re-computation latency or exhausting local GPU VRAM on repetitive LLM passes.
Sistem Diatesis Simetris & Alternasi Fokus Penderita Linguistik Teoretis
Jika rumpun Filipina seperti Tagalog mempertahankan sistem diatesis simetris penuh (fokus aktor, penderita, lokatif, dan instrumental dengan penanda kasus dan afiks morfologis yang tegas), bahasa Indonesia dan Melayu modern memanfaatkan alternasi aktif (meng-) dan penderita (di-, ter-, pasif persona) di mana fokus penderita (undergoer) merupakan ragam tuturan alami yang berfrekuensi tinggi, bukan sekadar pelemahan sintaksis pasif seperti pada bahasa Indo-Eropa.
Relevansi Pada Game: Terjemahan mesin komersial kerap memaksakan terjemahan harfiah pasif bahasa Inggris yang kaku ("telah diserang oleh"), merusak ritme tuturan dialog game. Pipeline kami membedakan pemetaan fokus simetris Tagalog dengan alternasi fokus penderita Indonesia/Melayu untuk menghasilkan subtitle yang padat, dinamis, dan alami sesuai batasan ruang layar game.
Kaskade Afiksasi Aglutinatif Morfosintaksis
Mekanisme morfologis di mana beberapa morfem terikat (awalan, sisipan, akhiran, dan konfiks seperti memper-...-kan, -an, -i, -kan) bertumpuk secara berurutan pada kata dasar untuk mengekspresikan aspek, modalitas, kausatif, dan transitivitas dengan presisi matematis.
Relevansi Pada Game: Pada game dengan variabel dinamis (seperti {PlayerName} menebas {Target}), variabel memengaruhi afiksasi kata dan memicu luluh fonem (hukum k, p, t, s). Penggantian kata biasa akan merusak tata bahasa; pipeline memerlukan aturan morfofonemik ketat untuk menjamin keutuhan kalimat.
Klitisasi (Proklitika & Enklitika) Morfologi
Morfem gramatikal yang secara sintaktis berfungsi sebagai kata ganti orang atau partikel penegas penuh tetapi secara fonologis melekat langsung pada kata induk tanpa spasi dan tanpa tekanan leksikal independen (ku-, -mu, -nya, -lah, -kah).
Relevansi Pada Game: Model LLM komersial kerap memunculkan spasi liar yang salah ("pedang nya", "ambil kan") atau gagal saat klitika harus menempel menembus tag pemformatan biner (<tag1>pedang</tag1>nya). Pipeline kami menjamin perekatan klitika yang presisi tanpa merusak batas tag engine game.
Stratifikasi Laras Bahasa & Diglosia Sosiolinguistik
Pemisahan sosiolinguistik yang tajam antara Ragam Tinggi (Bahasa Baku resmi/sastra) dan Ragam Rendah (Bahasa Gaul santai, prokem anak muda Jakarta, Bahasa Pasar, dan campur kode Taglish).
Relevansi Pada Game: Terjemahan mesin generik selalu terjebak pada bahasa baku kaku buku pelajaran sekolah di setiap percakapan. LoRA Adaptif Laras kami secara dinamis memastikan prajurit perang berbicara dengan slang bahasa gaul yang natural, sementara dokumen arsip kuno tetap mempertahankan wibawa sastra tinggi.
Kalibrasi Sigmoid Platt NLP Statistik
Teknik kalibrasi statistik (P(Fidelity|s) = 1 / (1 + e^-(A·s + B))) yang memetakan skor kemiripan kosinus bi-encoder mentah ke dalam probabilitas posterior empiris, dilatih pada korpus validasi beranotasi manusia (5.000+ segmen bilingual ID, MS, TL).
Relevansi Pada Game: Jarak kosinus vektor mentah bergeser secara non-linear lintas pasangan bahasa. Kalibrasi Platt menormalisasi skor sehingga mencerminkan probabilitas empiris kesetaraan semantik (makna), bukan sekadar angka kemiripan vektor arbitrer. Bi-encoder E5 difokuskan untuk mengukur kesetiaan makna (semantic fidelity), sedangkan keluwesan laras dan slang dikelola secara terpisah oleh LoRA dan stylist multi-tahap.
Tokenisasi Leksikal Bijektif Teori Bahasa Formal
Pemetaan matematis ketat f: X → Y yang bersifat satu-satu (injektif) dan pada (surjektif). Kode kontrol internal game, tag warna teks, dan variabel diabstraksikan menjadi placeholder standar <tagN>.
Relevansi Pada Game: Sifat bijektif ini menjamin setiap kode biner engine dipetakan ke tepat satu token neural dan dapat dikembalikan sehabis terjemahan tanpa ada kode yang hilang, tertukar, atau merusak sintaks runtime game.
Penyelarasan Kombinatorik Leave-One-Out Optimasi Algoritma
Algoritma pencarian restorasi sintaks yang secara sistematis menyisihkan satu tag format pada satu waktu untuk mengukur dampak marjinalnya terhadap hilangnya keselarasan semantik vektor bi-encoder.
Relevansi Pada Game: Mencegah kesalahan penempatan tag yang terburu-buru (greedy) dan mampu menentukan titik koordinat tag yang tepat bahkan ketika LLM menggeser tanda baca, membalik klausa, atau menghilangkan kode jeda baris.
Remediasi Multi-Tahap Terikat-Sandwich Generasi Terbatas
Pipeline koreksi multi-tahap di mana penyesuaian gaya bahasa (injeksi slang, nada emosional santai) diapit di antara gerbang validasi batas struktur yang sangat ketat.
Relevansi Pada Game: Jika re-terjemahan gaya bahasa melanggar batas byte memori game atau merusak batasan token, sistem otomatis membatalkan perubahan (rollback) seketika ke hasil tahap pertama yang sudah terbukti aman secara struktural.
Kompilasi 'Text-First' Terdekoplasi Sistem Perangkat Lunak
Pemisahan arsitektural antara aset terjemahan dengan file instalasi fisik game. Pipeline kompilasi hanya memproduksi paket .karyain terenkripsi Brotli-11 yang sangat ringan, memuat pohon delta teks, matriks kapabilitas (caps), dan topologi bahasa (slots).
Relevansi Pada Game: Menghilangkan kebutuhan untuk mengepak ulang arsip raksasa berukuran puluhan gigabyte (RPKG, Forge, BigPC) di workstation build lokal, memangkas durasi pengemasan dari berjam-jam menjadi di bawah 5 detik.
Bedah Biner In-Situ, Idempotensi & Invertibilitas Rekayasa Biner Terbalik
Penambalan biner dan struktur memori pada PC pengguna oleh Universal Patcher berbasis C# .NET 8 murni yang dieksekusi melalui alokasi streaming memori tanpa menulis berkas biner sementara yang tak bertanda tangan ke disk, serta ditandatangani Authenticode SHA-256. Patcher menghitung ulang pointer, mengalokasikan tabel string, dan mengelola overlay VFS secara dinamis.
Relevansi Pada Game: Menjamin prinsip idempotensi matematis f(f(x)) = f(x) sehingga eksekusi patch berulang menghasilkan kondisi aman yang identik tanpa duplikasi string atau pergeseran pointer, sekaligus menjamin invertibilitas matematis f⁻¹(f(x)) = x melalui manifest backup byte-exact *.bakaryain untuk pemulihan sempurna saat uninstal atau pembaruan game resmi.
Pengindeksan Vektor Semantik & Cache Trinity Basis Data Vektor
Arsitektur cache lokal berkinerja tinggi yang memadukan kumpulan tensor PyTorch fp16 (trinity_cache.pt) dan indeks FAISS Inner Product (trinity_vector.faiss) berisi lebih dari 3 juta embedding vektor, membekukan hasil penjangkaran kanon pre-flight ke dalam memori workstation lokal.
Relevansi Pada Game: Menghadirkan kecepatan pencarian vektor arketipe karakter, nada emosional, dan peristilahan di bawah 1 milidetik tanpa beban komputasi ulang atau fragmentasi VRAM lokal saat inferensi batch.

Released Archive

Austronesian Showcase

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