4.6
36 条评分
★★★★★
2025年8月18日
2015年4月25日
更新内容
v2.3• Refreshed Learn Hindi – Phrasebook interface. • Faster and smoother learning experience. • Bug fixes and performance improvements.
应用信息
- 开发者
- Webron Software LTD
- 分类
- Travel
- 价格
- 免费
- 版本
- 2.3
- App ID
- 976056746
简介
Learn Hindi is an easy to use mobile Hindi phrasebook that will give visitors to India and those who are interested in learning Hindi a good start in the language. Learn Hindi is recorded using a native speaker and we have tried our best to be authentic in the pronunciation whilst ensuring it is easy to understand. Recommended app for tourists and business people visiting India. Features: • Universal app works on iPhone, iPod Touch, & iPad • Carefully translated list of essential phrases • 300+ common words and phrases included for FREE • Upgrade and unlock all 1,600+ phrases in 18 categories • Audio recorded by native speakers • Option to playback audio at slower speed • No internet connection required • Highlight important words with tips • Store frequently used phrases in favourites • Search by words inside the app • No adverts or annoying popups CATEGORIES FREE Categories: * Greetings * General conversation * Numbers * Time and date * Directions and places * Transportation * Emergency PRO Categories: * Accommodation * Eating out * Shopping * Colours * Towns and provinces * Countries * Tourist attractions * Family * Dating * Feeling sick * Tongue twisters • HOW TO RESTORE PURCHASES? Purchases are one-time and carry over between devices. To restore your purchases on a new device, tap on PRO badge on one of the locked categories, tap on the Restore Purchase button. Even if you forget to do this step and try to buy the app again, it will be restored for free. THANKS FOR ALL THE SUPPORT IF YOU LIKE THE APP PLEASE LEAVE A REVIEW :-) Privacy Policy: https://www.webronsoftware.co.uk/mobile-apps/learn-language/privacy-policy Terms of Use: https://www.webronsoftware.co.uk/mobile-apps/learn-language/terms-of-use
下载量预测
预估总下载量
13
低 / 月
20
预估 / 月
38
高 / 月
基于评分数量 ÷ 类别评分率估算,实际下载量误差可达 ±50%,与 Sensor Tower 方法一致。
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