How to Evaluate Text-to-Speech Models for Voice AI Applications: Insights from Cartesia
Blog post from Coval
In the competitive landscape of voice AI, selecting the appropriate text-to-speech (TTS) model is crucial for businesses developing voice agents, with options ranging from major providers like OpenAI and Google to specialized players like Cartesia. The complexity of the voice AI technology stack, which includes components such as speech-to-text, LLM processing, and turn detection, requires careful evaluation, particularly for the subjective and customer-facing TTS element. Key factors in choosing a TTS solution include voice naturalism and quality, performance and latency, controllability and emotional intelligence, pronunciation accuracy, and enterprise readiness. Each factor significantly impacts user engagement, operational costs, and overall business success. Coval offers comprehensive evaluation and optimization services, including simulation, testing, and live monitoring, to ensure businesses select TTS providers that align with their specific needs and maintain high-quality voice experiences. This approach helps businesses navigate the evolving TTS landscape, balancing technical requirements with the subjective experience of brand representation through voice.
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