Bahasa Indonesia, Melayu, Filipino
Memuat data interpretasi naratif secara real-time...
The Full Story
Pywel itu tempat yang kejam, bro. Gak cuma urusan bacok-bacokan, tapi soal ngerti kenapa si Kliff ini pusing setengah mati ngurusin sisa-sisa pasukannya. Crimson Desert nawarin dunia open world yang luas banget, dari gunung salju sampe kastil megah, tapi ceritanya bakal hambar kalau lu cuma baca teks Inggris standar yang kaku. Di sini lah mod lokalisasi gue masuk buat nyelamatin waktu main lu.
Bayangin 792.607 kata diproses pake pipeline neural 8 tahap biar gaya bahasanya nggak 'template banget'. Karakter preman di Pywel bakal ngomong sekasar temen tongkrongan lu, sementara para Ksatria ngomongnya bakal tetep berwibawa. Gue jamin deh, feel-nya beda jauh sama translate otomatis yang bikin puyeng. Skor kemiripan semantiknya tembus 87% buat Bahasa Indonesia, jadi nggak bakal ada kalimat absurd 'pergi ke mana saya tidak tahu'. Udah, nggak usah mikir lama-lama, sikat modnya biar main makin greget!
Experimental Build
Author's Notes
This translation mod is using patcher, so it will work for every version.
=== Audit Teknis & Semantik Lokalisasi CRIMSON DESERT ===
1. SKALA LINGUISTIK & CAKUPAN
- Skala Proyek: Sekitar 792,607 kata diproses melalui alur neural 8-tahap.
- Cakupan Bahasa: Dukungan trilingual penuh untuk pasar Indonesia, Malaysia, dan Filipina.
- Status Kelengkapan: Indonesia: 88.1%, Malay: 91.5%, Filipino: 87.6%
- Analisis Variasi Leksikal: Source -> Density: 66.1% | Diversity: 2.5%, Indonesia -> Density: 74.9% | Diversity: 3.3%, Malay -> Density: 73.8% | Diversity: 2.6%, Filipino -> Density: 60.7% | Diversity: 3.2%
2. VALIDASI NEURAL & AKURASI
- Skor Keselarasan Semantik (Platt Score): Indonesia: 87%, 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 238 karakter unik.
- Pemulihan Struktur Otomatis (Tag Repair): 316 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 2.8% 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