Bahasa Indonesia, Melayu, Filipino
Download mod translasi Indonesia FF Tactics: The Ivalice Chronicles terlengkap dengan 248rb kata hasil engine AI neural adaptif!
The Full Story
Pusing baca dialog ksatria Ivalice yang bahasanya selangit? Gak usah khawatir! Gue udah ngeracik mod lokalisasi raksasa 248.732 kata pake engine AI neural 8 tahap biar Ramza dan kawan-kawan ngomong pake bahasa yang ngena di hati kita. Dari omongan formal para bangsawan sampe slang kasar para bandit, semuanya dapet sentuhan kearifan lokal yang otentik. Ingat ya, ini masih Alpha Eksperimental jadi masih ada watermark-nya dikit dan gue butuh bantuan lu buat laporin kalo ada terjemahan yang aneh. Sikat mod-nya sekarang, nikmati ceritanya, dan mari kita lestarikan legenda Ivalice bareng-bareng!
Experimental Build
Author's Notes
=== Audit Teknis & Semantik Lokalisasi FF Tactics the Ivalice Chronicles === 1. SKALA LINGUISTIK & CAKUPAN - Skala Proyek: Sekitar 248,732 kata diproses melalui alur neural 8-tahap. - Cakupan Bahasa: Dukungan trilingual penuh untuk pasar Indonesia, Malaysia, dan Filipina. - Status Build: Experimental Alpha — watermarked preview build. - Status Kelengkapan: Indonesia: 96.6%, Malay: 96.6%, Filipino: 96.4% - Analisis Variasi Leksikal: Source -> Density: 64.8% | Diversity: 4.6%, Indonesia -> Density: 74.6% | Diversity: 5.9%, Malay -> Density: 75.8% | Diversity: 5.3%, Filipino -> Density: 60.9% | Diversity: 5.2% 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 131 karakter unik. - Pemulihan Struktur Otomatis (Tag Repair): 0 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 2.3% watermarks. Support this project on Trakteer or Ko-fi to download NON-WATERMARKED version.
Comments
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.
Name
Narrative Profile
Associated Entities
Semantic Archetypes
NLP Pipeline Intelligence