Introduction

Building effective voice AI systems requires a comprehensive approach that balances controllability, user experience, and system responsiveness. This guide outlines a framework designed to optimize human-like voice agents in platforms like Assistable, incorporating speech synthesis, phonetic control, and performance tuning.

1. Speech Controllability and Customization

• Voice Selection: Choose a voice that matches the context of the interaction.
• Pronunciation Control: Use tools like the CMU Pronouncing Dictionary or IPA transcription for correct pronunciation.
  • http://www.speech.cs.cmu.edu/cgi-bin/cmudict/
  • https://tophonetics.com/
• Pacing and Pausing: Insert hyphens to add pauses, improving naturalness and comprehension.

2. Text Normalization for Consistency

Convert raw text, especially numbers, dates, and currency, into spoken form to avoid errors in AI pronunciation.

3. Temperature Control for Emotion and Tone

Adjust the temperature to control the stability or expressiveness of the voice. Lower temperatures produce a more formal tone, while higher temperatures result in more dynamic speech and erratic tone, volume, and pacing.

4. Latency vs. User Experience

Balance features and responsiveness, considering the trade-off between latency and functionality. Prioritize real-time responses for customer service but allow slight delays for more consistent and accurate outputs.

5. Audio Speed and Emotion

• Speed Adjustments: Control the overall speed of the agent's speech to match the type of interaction.
• Emotional Tone Control: Use voice temperature settings to modulate emotion.

6. Advanced Customizations

• Ambient Sound: Add background noise to simulate real-world environments, improving immersion during casual interactions.
• Function Calling: Integrate APIs for real-time interactions to enhance adaptability and interactivity.
  • Utilize your understanding of AI voice capabilities to identify functional limits and operate within those boundaries to minimize errors.

7. Iterative Improvement and User Feedback

Continuously gather user feedback and make adjustments to pronunciation, pacing, or tone as needed. Periodically adjust and fine-tune aspects like voice temperature and speed to better match specific interaction requirements.