Time to First Audio: Measuring and Reducing TTS Latency in Voice Agents
Blog post from Gradium
Voice agents aim to match the natural conversational gap of around 200 milliseconds between exchanges, necessitating efficient architectures when utilizing components like speech-to-text, large language models, and text-to-speech (TTS) systems. A critical metric in TTS is Time to First Audio (TTFA), which measures the time from request to the first playable audio sample, a factor greatly influenced by streaming APIs that often transmit metadata before actual audio. Accurate TTFA measurement requires bypassing initial metadata to timestamp the first real audio byte, as differences in network latency, server location, and streaming capabilities can significantly affect performance. Gradium, a TTS provider, has developed an efficient pipeline that surpasses competitors like ElevenLabs, Mistral, and OpenAI in delivering first audio, optimizing TTFA with Delayed Streams Modeling architecture, CUDA graph optimization, and streaming LLM output directly into TTS. This performance advantage allows Gradium to maintain high voice quality while also offering various deployment options to suit different infrastructure needs, from cloud APIs to on-premises solutions, ensuring flexibility and compliance with data sovereignty requirements. While latency is a crucial aspect, a comprehensive voice agent also requires natural-sounding output and effective orchestration to handle streaming and conversational dynamics, which Gradium also aims to address within its full-stack design.
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