AI BriefingText to Speech API Integration Guide
Key point
This explains three approaches and architectural decision factors for efficiently integrating and scaling ElevenLabs' Text to Speech API.
Details
When integrating ElevenLabs' Text to Speech API, you need to consider transport mode, model and output format selection, streaming method, concurrency limit management, and caching and retry strategies.
The API can be called in three ways depending on the use case:
- Batch (convert): A method that receives the entire audio in a single request. It is the simplest to implement, but has the longest Time-to-first-audio. It is suitable for offline rendering such as audiobook production.
- HTTP streaming (stream): Delivers the response in chunks. It is easy to implement and has short perceived latency, making it suitable for general playback in web or app environments.
- WebSocket (stream-input): A method that maintains a connection while progressively sending text and receiving audio. It is optimized for implementing AI agents that need to convert LLM output into speech in real time.
For efficient operation, it is recommended to implement retry logic with Exponential Backoff and Full Jitter applied right before hitting concurrency limits, and to Cache a hash value of the output parameters for the same text so that duplicate costs are not incurred.
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