Adora Magic City International Cruise

Background

Adora Magic City is China’s first domestically built large cruise ship, built by CSSC and operated by Adora Cruises. Gross tonnage 135,500; capacity 5,246 passengers. Crew and staff from 30+ countries; over 60% non-Chinese. Job-oriented Chinese training for non-Chinese staff is essential for service quality and operations.

Project overview

Project: Adora Magic City Job Chinese Training for Non-Chinese Staff
Partners: Adora Cruises, Baizor International Chinese AI Lab
Target: Cabin, F&B, housekeeping, entertainment staff
Setting: Shipboard mobile classroom, job Chinese training, service scenario simulation

Challenges

• Language barrier: Staff from Southeast Asia, Europe, South America lacked basic Chinese
• Job terminology: F&B, housekeeping, safety required specialized Chinese
• Complex scenarios: Diverse passenger needs and emergencies
• Limited training time: Short port stays made centralized training difficult
• Assessment: Traditional training lacked effective assessment

Solution

Baizor platform customized for job Chinese:

1. Scenario-based job Chinese courses — F&B (ordering, serving, complaints); housekeeping (check-in, cleaning, requests); safety (emergency broadcast, evacuation, medical); entertainment (introductions, games, culture).

2. AI assessment and pronunciation — Real-time speech assessment (fluency, completeness, accuracy, tone); automatic correction feedback; dialogue simulation for service scenarios.

3. Fragmented learning — Mobile platform; offline mode for unstable connectivity; 3–5 min micro-courses.

4. Management and assessment — Level-based assessment by job requirement; progress tracking; certificate upon passing.

Core technologies

• Speech recognition and assessment (multi-accent), NLP (dialogue generation), adaptive recommendation, multimodal teaching, offline sync

Results

• Improved Chinese: 80% of non-Chinese staff reached basic job Chinese in 3 months
• Better service: Passenger satisfaction up 25% after Chinese improvement
• Lower cost: 60% reduction in training time and cost vs. traditional
• Flexible learning: Fits fragmented time without affecting work schedule