Principle:Elevenlabs Elevenlabs python Realtime Text to Speech
| Knowledge Sources | |
|---|---|
| Domains | Speech_Synthesis, Streaming, WebSocket |
| Last Updated | 2026-02-15 00:00 GMT |
Overview
A streaming synthesis technique that converts incrementally arriving text into speech audio in real time over a persistent WebSocket connection, enabling low-latency audio output as text is generated.
Description
Realtime Text-to-Speech solves the latency problem inherent in batch TTS by establishing a bidirectional WebSocket connection to the synthesis server. Instead of waiting for the complete text, the client sends text chunks as they become available (e.g., from an LLM stream) and receives audio chunks back immediately. This enables "first-byte" audio playback while text is still being generated.
The technique involves three phases:
- Connection setup: Open WebSocket with voice settings and generation config
- Streaming loop: Send text chunks (buffered at sentence boundaries), receive base64-encoded audio chunks via non-blocking receive
- Flush and drain: Send empty text to signal end-of-input, then collect remaining audio until connection closes
This is fundamentally different from the REST-based TTS convert method, which requires the complete text upfront.
Usage
Use this principle when text is generated incrementally (e.g., streaming from an LLM, real-time user input, or progressive text sources) and you need audio playback to begin before all text is available. This is the optimal choice for chatbot interfaces, live narration, and interactive applications where latency matters.
Theoretical Basis
Realtime TTS follows a producer-consumer streaming pattern over WebSocket:
# Abstract pattern (NOT actual implementation)
ws = websocket_connect(tts_endpoint, voice_id, model_id)
ws.send(initial_config) # voice_settings, generation_config
for chunk in text_chunker(text_stream):
ws.send(chunk)
audio = ws.recv(timeout=10ms) # Non-blocking
if audio:
yield decode(audio)
ws.send(flush_signal) # Empty text = end of input
while not connection_closed:
audio = ws.recv() # Blocking drain
yield decode(audio)
Key design decisions:
- Text chunking at sentence boundaries: Ensures coherent prosody within each audio segment
- Non-blocking receive during send: Allows audio to arrive while still sending text
- Flush + blocking drain: Ensures all remaining audio is collected after input ends