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The dialect support feature of Qwen-TTS can effectively solve this problem, and the implementation steps are as follows:
- Identify user groupsFirst of all, we need to count the distribution of dialects in the service area, focusing on the three supported dialects: Beijing dialect, Shanghainese dialect, and Sichuan dialect.
- Multi-dialect speech library deployment: Create a dialect voice library by setting different voice parameters (Dylan/Jada/Sunny) in API calls.
- Intelligent Matching Strategy: Automatically switches the corresponding dialect version according to the user's IP or language preference settings.
- Mixed use program: A hybrid model of "Putonghua + dialectal keywords" can be used for some of the content, with dialectal pronunciation retained for key terms.
Implementation examples: E-commerce platforms can use Qwen-TTS in order status reminders, and enable Dylan's voice notification of "Your parcel has arrived at the Caijiao Station" for Beijing users to ensure that information is conveyed in a more friendly and natural way.
This answer comes from the articleQwen-TTS: Speech Synthesis Tool with Chinese Dialect and Bilingual SupportThe
May not be reproduced without permission:AI productivity tools " How to solve the problem of voice assistant comprehension barriers for users in multi-dialect areas?
