Fish Audio raises $50M seed to build AI voice models for creators and enterprises
The market for AI-generated voice models is massive. Creative use cases require AI voice models to be more expressive, while enterprises looking to automate customer
The market for AI-generated voice models is massive. Creative use cases require AI voice models to be more expressive, while enterprises looking to automate customer support and sales ops need them to be more steerable. Palo Alto-based Fish Audio wants to cater to all of those use cases with its library of more than 15,000 natural language controls. Since launching last year, the startup today has more than 8 million people using the open-source or hosted versions of its models, and now generates annual recurring revenue of $21 million. To continue building on that traction, the startup on Tuesday said it has raised $50 million in a seed round that was led by Coreline Ventures and Capital Today. The funding also saw participation from 359 Capital, Parable, Play Time, Alphalist Partners, Bayhouse Ventures, Carya Venture Partners, and HF0. Fish Audio started as a small project by former NVIDIA researcher Shijia Liao, who, frustrated by non-expressive synthetic voices available on the market, trained a voice generation model on a single GPU, which he open-sourced. The Fish Speech repository on GitHub now has more than 31,000 stars, and is used by indie developers, video game designers, and creators.
The company has launched five models in the last year: four speech generation models and one speech-to-text model. It has open-sourced three of its speech generation models, but its latest S2.1 Pro model is available only through its paid API. Fish Audio offers paid monthly plans suited for creators and teams that unlock a set number of minutes of generation, plus voice cloning features. The company also offers an enterprise version of its APIs and platform, and says organizations like HeyGen, Sanas and Plaud are already using it. âEvery enterprise has different use cases and different preferences. For example, companies like HeyGen, which use our voices to power AI avatars, want realism in voices; a gaming studio would want expressive voice for their characters; and voice agent companies like LiveKit want more natural-sounding and low-latency voices that are expressive enough for calls,â Cao said. One way the startup has built its library of voices is by simply asking users to submit their own voices for training its models, and compensating them if their voices are used. That resulted in some trouble a few months ago, however, as some creators alleged that their voices were uploaded to Fish Audio without their consent.
The startup had a DMCA content take-down process in place to address such concerns, but the take-downs themselves took a long time. Fish Audioâs CEO and co-founder Rissa Cao told TechCrunch that the company has now automated the take-down process. Creators can easily submit a short voice sample or a contract to prove that an uploaded voice belongs to them, and their voice will be taken off the startupâs platform in less than 3 minutes, she said. Still, that doesnât prevent anyone from uploading an artistâs voice without their knowledge. And until the artist finds out, their voice will continue to be used on the platform until they file for it to be taken down. Oskue Honda, a partner at Coreline Ventures, said a community-driven model only works when creators trust the platform. âA community-centric approach can only become a durable advantage if creators trust the platform. That means consent, transparency, and attribution must be built into the product rather than treated as afterthoughts. I believe the industry needs to move toward verified voice ownership, clear licensing terms, easy reporting and takedown processes, and eventually revenue-sharing models where creators benefit financially when their voices are licensed or used commercially,â he said.
