ElevenLabs is the best text-to-speech AI system (engineering.kablamo.com.au)

For the Cerebral Palsy Alliance’s My Voice Library (MVL), ElevenLabs emerged as the top text-to-speech (TTS) system after side-by-side tests with AWS Polly, Google Cloud, Azure TTS and Murf.ai. Teams judged ElevenLabs voices as the most natural, emotionally expressive and easiest to integrate — critical for MVL’s goal of creating multilingual, reusable character voices for children with dysarthria. The switch to an AI TTS reduced studio costs, simplified internationalization and solved continuity risks from human voice actors while delivering production-quality results good enough for deployment. Technically, the team used ElevenLabs’ Python client and the eleven_multilingual_v2 model (v2 cited as the most stable; v3 produced random artifacts), tuning VoiceSettings like speed (e.g., 1.1) and stability (≈0.7). Best practices included crafting detailed “personas” to steer tone, caching generated audio to control costs, and rigorous manual listening to catch phonetic edge cases (individual plosives, singing/scale generation issues). They also demonstrated convincing voice cloning from existing studio recordings in small tests. Implications for AI/ML: modern TTS can match studio quality for many assistive applications, but teams must manage model versioning, prompt/persona engineering, cost-aware caching and ongoing manual QA to handle language- and sound-specific edge cases.