Hi Everyone!
Solving AI audio end-to-end means tackling both generation and understanding - from text-to-speech to speech-to-text and everything in between. At ElevenLabs, we re working on breakthroughs in AI audio that bridge research and real-world use.
Ask me anything about what we re building, the challenges of scaling AI speech models, and where this space is headed. Also keen to hear what you ve built with ElevenLabs! 

Hey @ElevenLabs! The voice quality is miles ahead of anything else we've tried. Huge fan of what you guys are building! We re actually using it in our internal tool to generate audio summaries of specific Spotify topics. It works like magic, but we ve noticed one tiny hiccup: the audio occasionally fades out or loses volume mid-sentence. Has anyone else experienced this, or is there a specific API parameter we should look into to keep it consistent? Keep up the great work, looking forward to seeing where you take the product next!

I'm trying to create realistic audio to support scenarios for frontline staff in homeless shelters and housing working with clients. The challenge is finding realistic voices that have a wide range of emotional affect. We are hoping to find a generative approach to developing multiple voices rather than creating voices with actors or ourselves. We've tried v3 Voice Design which expands on monotone generated voices but not much. We want voices that go from soft whispers to screaming and everything in between. Perhaps I'm not very good at prompting, but I've tried various attempts. Again, we're trying to do this without needing to record every voice which is not sustainable for our approach. Any recommendations? Thanks!