A New Framework for Evaluating Voice Agents (EVA)
Conversational voice agents present a distinct evaluation challenge: they must simultaneously satisfy two objectives — accuracy (completing the user’s task correctly and faithfully) and conversational experience (doing so naturally, concisely, and in a way appropriate for spoken interaction). These objectives are deeply intertwined: mishearing a confirmation code renders perfect LLM reasoning meaningless, a wall of options overwhelms a caller who can’t skim spoken output, and delayed responses can pass every accuracy check while remaining unusable in practice. Existing frameworks treat […]
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