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Taiwan Pulse adopted the SIRAYA AI Voice Solution<\/strong> to build an AI-powered phone survey system that combines Large Language Models (LLMs), Speech-to-Text (ASR), Text-to-Speech (TTS), and low-latency communication capabilities to automate large-scale phone interviews.<\/em><\/p>\n\n\n\n Taiwan Pulse is a Taiwan-based research firm specializing in market research and public opinion polling, serving political, municipal, and commercial research needs.<\/p>\n\n\n\n Traditional phone surveys rely heavily on human interviewers, resulting in high labor costs, recruitment challenges, and lengthy survey cycles. Depending on the number of respondents and questions, a typical survey takes around 5\u20137 days to complete.<\/p>\n\n\n\n Survey demand also fluctuates significantly. During election periods, multiple counties, cities, districts, and candidates may require surveys at the same time, with demand potentially increasing 1\u20132 times compared with non-election periods. Scaling a traditional interviewer-based operation quickly can therefore be challenging.<\/p>\n\n\n\n Language is another consideration. Some respondents, particularly older populations, are more comfortable communicating in Taiwanese, while younger interviewers are increasingly less familiar with the language. This creates an additional challenge for traditional phone-based research.<\/p>\n\n\n\n Taiwan Pulse therefore needed a more scalable approach that could handle large volumes of calls while maintaining a natural conversation experience and reducing reliance on human interviewers.<\/p>\n\n\n\n SIRAYA built a customized AI phone survey system for Taiwan Pulse, combining speech recognition, speech generation, Large Language Models, and real-time communication capabilities. The AI Agent manages the complete survey workflow, from automated outbound dialing and voice interaction to response understanding and questionnaire flow control.<\/p>\n\n\n\n Compared with traditional phone surveys constrained by interviewer availability and working hours, the AI Voice Agent can handle large numbers of outbound calls simultaneously and conduct conversations based on predefined questionnaires and respondent responses.<\/p>\n\n\n\n The system integrates multiple AI capabilities:<\/p>\n\n\n\n For a survey application, simply generating an answer is not enough. The AI needs to understand context, keep the conversation on track, and follow the questionnaire consistently. SIRAYA therefore optimized the system to:<\/p>\n\n\n\n In actual use, AI response latency is approximately 0.5\u20130.8 second, approaching the response time of natural human conversations and minimizing noticeable delays for respondents.<\/p>\n\n\n\n The solution also supports Taiwanese-language conversations, combining speech recognition and language model capabilities to better understand respondents across different age groups and language backgrounds.<\/p>\n\n\n\n After adopting the SIRAYA AI Voice Solution, Taiwan Pulse improved survey efficiency, scalability, and operational flexibility:<\/p>\n\n\n\n More importantly, Taiwan Pulse has established a scalable AI survey infrastructure that shifts its operations from reliance on human interviewer capacity toward a more flexible and efficient AI-driven model.<\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>\n\n\n\n <\/p>","protected":false},"featured_media":7468,"parent":0,"menu_order":0,"template":"","class_list":["post-7467","case-studies","type-case-studies","status-publish","has-post-thumbnail","hentry"],"acf":[],"yoast_head":"\nOverview<\/h2>\n\n\n\n
AI-Powered Voice Survey Solution<\/h2>\n\n\n\n
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AI-powered phone automation reduces manual effort and repetitive work, improving research efficiency while optimizing overall execution costs.
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Nearly 30,000 phone interviews can be completed within 1\u20132 days.
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Enables large-scale, multi-region surveys to run simultaneously during peak periods such as elections.
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Supports Taiwanese-language conversations while standardized AI workflows reduce interviewer variation and inconsistencies in interview records.<\/li>\n<\/ul>\n\n\n\n