Bahasa Indonesia, Melayu, Filipino
Memuat data interpretasi naratif secara real-time...
The Full Story
Jelajahi keajaiban Solistia dalam Octopath Traveler 2, mahakarya JRPG yang menceritakan petualangan delapan karakter unik dengan visual HD-2D yang sangat indah. Dari aksi 'Scent of Commerce' si Partitio sampai perjuangan berdarah Hikari, tiap langkahmu adalah cerita legendaris.
Kenapa harus pake mod ini? Karena ini bukan hasil Google Translate yang kaku! Kami pake teknologi gila '8-stage neural pipeline' buat menerjemahkan 340.062 kata ke Bahasa Indonesia yang asik, gaul, dan nyambung sama budaya kita. Tiap karakter punya gaya ngomong sendiri—ada yang formal, ada yang 'raw' alias santai banget. Dengan tingkat akurasi 86% dan ribuan tag error yang udah dibenahin, petualangan Hikari dkk bakal berasa lokal banget di telinga kamu. Langsung sikat, partner!
Experimental Build
Author's Notes
Maybe some lines are still broken, not much, only 0.05% roughly. I have hard times fixing it using pipeline.
=== Audit Teknis & Semantik Lokalisasi OCTOPATH TRAVELER 2 ===
1. SKALA LINGUISTIK & CAKUPAN
- Skala Proyek: Sekitar 340,062 kata diproses melalui alur neural 8-tahap.
- Cakupan Bahasa: Dukungan trilingual penuh untuk pasar Indonesia, Malaysia, dan Filipina.
- Status Kelengkapan: Indonesia: 96.9%, Malay: 97.0%, Filipino: 96.6%
- Analisis Variasi Leksikal: Source -> Density: 63.1% | Diversity: 3.7%, Indonesia -> Density: 72.8% | Diversity: 4.9%, Malay -> Density: 72.3% | Diversity: 3.6%, Filipino -> Density: 60.7% | Diversity: 4.5%
2. VALIDASI NEURAL & AKURASI
- Skor Keselarasan Semantik (Platt Score): Indonesia: 86%, Malay: 85%, Filipino: 84%
(Skor ini mengukur seberapa akurat terjemahan mempertahankan makna asli dari teks sumber.)
- Gaya Bahasa Karakter: Penyesuaian gaya (gaul, formal, santai) telah diterapkan pada 578 karakter unik.
- Pemulihan Struktur Otomatis (Tag Repair): 2951 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.
Attention: This version contains 4.2% watermarks. Support this project on Trakteer or Ko-fi to download NON-WATERMARKED version.
Linguistic Analysis Report
Discourse analysis using Gemma embeddings. Classifies rhetorical register across the corpus to ensure tonal consistency with source narrative assets.
Emotional tone mapped via dot-product similarity between extracted dialog embeddings and predefined sentiment anchors using zero-shot semantic alignment.
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.
* Sim = Cosine Similarity (Vector Space) · Density = Content/Total Tokens · Diversity = TTR (Type-Token Ratio) · "src" = Source Baseline · Named Entities enforced via GLiNER mining.
Heuristic markup verification utilizing multi-pass validation and correction to ensure syntactical integrity of control codes and visual tags.
Name
Narrative Profile
Associated Entities
Semantic Archetypes
NLP Pipeline Intelligence