Text-to-Speech APIs in 2026: Blind-Test Ranks and the Real Cost of 5M Characters

Description and use

Choosing a TTS API requires text normalization to avoid mispronunciation of abbreviations and phone numbers, and to accurately calculate costs for 5 M characters per month.

Problem

Choosing a TTS API is not trivial because invoices are metered per character, users notice pauses before the first word, and models mispronounce abbreviations like "Dr." and "Tue."

Outcome

Normalizing text before synthesis eliminates mispronunciations of abbreviations and phone numbers, improves user experience, and ensures accurate billing for high‑volume TTS usage.

Workflow

• 1. Identify the TTS use case and volume (5 M characters/month).
• 2. Gather pricing and quality data from vendors (Eleven v4, OpenAI, Kokoro‑82M, Piper, Cartesia Sonic).
• 3. Run a sample reminder through the chosen models and transcribe the output with faster‑whisper to detect mispronunciations.
• 4. Observe that "Tue." and "Dr." are misread and phone numbers are scrambled.
• 5. Write a Python function expand() that replaces abbreviated days/months, expands "Dr." to "Doctor", and formats phone numbers with pauses.
• 6. Apply expand() to all scripts before sending to the TTS API.
• 7. Verify that the models now pronounce "Tuesday, October 13" and a dialable number.
• 8. Recalculate cost based on 5 M characters/month and vendor pricing.
• 9. Document the workflow and share results in a report.

Evidence

Both turned the weekday into a number, and Kokoro scrambled the phone number into something nobody can dial.

Source

After normalizing, both models came back with "Tuesday, October 13" and a dialable number.

Source

Eleven v4 Turbo sits at the top of the arena with 1334 Elo, and Eleven v4 is right behind it at 1321.

Source