#Inequality in Language Recognition technology Language recognition technology does have unequal treatment of users in non-English-speaking countries, which is mainly manifested in the following aspects: 1. **Uneven resource allocation**: The R&D resources, data set scale and technical investment of the English language recognition system far exceed that of other languages, resulting in obvious performance differences. 2. **Difference in accuracy rate**: The recognition accuracy rate of English is usually higher than that of non-English languages, especially for small languages, dialects, and languages with accents. The recognition effect is worse. 3. **Technical adaptability**: Many language recognition systems are designed based on the characteristics of the English language, and the phonological, grammatical and cultural characteristics of other languages are not fully considered. 4. **Widening Digital divide**: This inequality has exacerbated the global digital divide and restricted the opportunity for non-English-speaking people to enjoy the dividends of AI technology equally. In recent years, major technology companies have begun to pay attention to multilingual equality and increase support for non-English languages and investment in research and development, but the gap still exists, and more global cooperation and localization efforts are needed to solve this problem.