Principle:Openai Openai python Text to Speech
| Knowledge Sources | |
|---|---|
| Domains | Audio, Speech_Synthesis |
| Last Updated | 2026-02-15 00:00 GMT |
Overview
A speech synthesis technique that converts text input into natural-sounding audio using neural voice models with configurable voice selection, speed, and output format.
Description
Text-to-speech (TTS) converts written text into spoken audio. Modern neural TTS models produce highly natural-sounding speech with multiple voice options, adjustable speed, and various output formats. The synthesis can be done in a single request (returning the complete audio file) or streamed for real-time playback as audio is generated.
Usage
Use this principle when you need to generate spoken audio from text content. Applications include voice assistants, accessibility features, audiobook generation, and content narration. Choose streaming mode for real-time playback in interactive applications.
Theoretical Basis
TTS follows a Text-to-Audio Pipeline:
# TTS generation flow
audio = synthesize(
text="Hello, world!",
model=tts_model, # Quality vs speed tradeoff
voice=voice_id, # Voice characteristics
speed=1.0, # Playback speed multiplier
format="mp3" # Output audio format
)
# Returns binary audio data
# Streaming variant for real-time playback
with synthesize_streaming(text, model, voice) as stream:
for audio_chunk in stream:
play(audio_chunk)