Building a Multi-Language Voice AI Agent: Automatic Language Detection for Restaurant Phone Systems
This article discusses the challenges of building a voice AI agent that can handle multiple languages for restaurant phone systems without requiring callers to select a language.
Why it matters
Automatic language detection is crucial for voice AI systems to provide a frictionless experience for callers in multilingual communities, which is common for many restaurants.
Key Points
- 1Developed a 3-stage language detection pipeline to automatically identify the caller's language
- 2Used speech-to-text output's language confidence score as the primary indicator, with contextual confirmation and mid-call switching
- 3Addressed the challenge of greeting callers in the right language, experimenting with different approaches
Details
The article describes how the team at RingFoods built an AI voice agent to handle restaurant phone calls in cities with diverse language communities. The key challenge was enabling seamless language detection without forcing callers to select a language option. The 3-stage detection pipeline uses the initial speech-to-text output's language confidence score, followed by contextual confirmation and monitoring for mid-call language switches. The team also explored different approaches to the greeting problem, including defaulting to English, using the restaurant's configured primary language, and leveraging caller ID history to greet in the preferred language.
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