TTS (Text-to-Speech)

Text-to-Speech (TTS) is the technology that converts written text into synthesized spoken audio. Modern neural TTS systems produce voices that are nearly indistinguishable from human speech, with natural prosody, appropriate pausing, and expressive intonation — critical to creating voice agents that feel trustworthy and pleasant to interact with.

TTS Technology Evolution

• Concatenative TTS (old): Stitches together pre-recorded speech units; sounds robotic and stilted.
• Statistical parametric TTS: Generates speech using statistical models; more natural than concatenative but still has artifacts.
• Neural TTS (modern): Uses deep neural networks trained on human speech; produces highly natural, expressive audio.

Leading Neural TTS Providers

• Google Cloud Text-to-Speech: 420+ voices across 130+ languages; natural prosody.
• OpenAI Text-to-Speech (TTS-1): Fast, high-quality; designed for real-time use.
• AWS Polly: 100+ voices; good customization and SSML support.
• Microsoft Azure Speech Services: Enterprise-grade; excellent for healthcare and financial services.

Voice Characteristics

Modern TTS engines allow customization of:

• Voice selection: Gender, age, accent, regional dialect.
• Speech rate: Fast or slow delivery; affects comprehension and tone.
• Pitch and intonation: Add emotion and emphasis (excited, concerned, professional).

TTS Latency

Streaming TTS can generate audio while the LLM is still generating text, minimizing end-to-end latency. This is essential for natural voice agent conversations (sub-800ms response time).

Workforce Wave TTS

Workforce Wave uses neural TTS with voice customization, allowing organizations to create branded voice agents. Streaming TTS ensures low latency and natural conversation flow.