TTS
~2 min read
Concept & How It Works
Why Does It Exist?
Reading agent responses on screen isn't always possible or desirable. TTS enables phone agents, accessibility features, and conversational experiences that feel human.
Real-World Analogy
TTS is an audiobook narrator — it reads written text aloud with appropriate pacing, emphasis, and tone.
Visual Workflows
What is TTS?
Example
Scenario
Agent generates answer text → TTS converts to audio stream → played through phone system IVR. Voice: 'professional female, en-US'.
Solution
In Voice & Multimodal Agents, apply TTS to this scenario: Agent generates answer text → TTS converts to audio stream → played through phone system IVR. Identify the inputs, run the technique, validate the output, and note one thing you would monitor in production.
Practice Task
Do this before moving to the next module — reading alone is not enough.
Open the Code Walkthrough below and run it locally. Change one parameter related to TTS (e.g. model, temperature, top_k, or tool name), observe the difference in output, and write 2–3 sentences explaining what changed.
Code Walkthrough
Highlighted lines show where TTS happens in the code.
1from openai import OpenAI # import dependencies2
3client = OpenAI() # create API client4
5def speak(text: str, output_path: str = "response.mp3") -> str: # define a reusable function6 response = client.audio.speech.create( # call the API7 model="tts-1",8 voice="nova",9 input=text,10 )11 response.stream_to_file(output_path)12 return output_path # return the resultCommands to Remember
Commands to Remember
pip install openai # vision, audio, and TTS APIspip install pypdf # PDF ingestion for document agents
Common Mistakes
- Treating TTS as a black box without evaluation
- Ignoring cost and latency in production
- Skipping error handling for tts
Cheat Sheet
Quick recap — the most important points from this module.
Cheat Sheet
quick ref- •TTS
- •Neural TTS
- •SSML
- •Voice ID