Recently, Oute AI has introduced a novel text-to-speech synthesis method called OuteTTS-0.1-350M. This method utilizes pure language modeling, eliminating the need for external adapters or complex architectures, offering a simplified TTS approach. Based on the LLaMa architecture, OuteTTS-0.1-350M uses WavTokenizer to directly generate audio tokens, making the process more efficient.
The model features zero-shot voice cloning capabilities, allowing it to replicate new voices with just a few seconds of reference audio. Designed for device performance, OuteTTS-0.1-350M is compatible with llama.cpp, making it an ideal choice for real-time applications. Despite its relatively small parameter size (350 million), its performance rivals that of larger, more complex TTS systems.
OuteTTS-0.1-350M's accessibility and efficiency make it suitable for a wide range of applications, including personalized assistants, audiobooks, and content localization. Oute AI has released it under the CC-BY license, encouraging further experimentation and integration into various projects, democratizing advanced TTS technology.
The release of OuteTTS-0.1-350M marks a significant step forward in text-to-speech technology, leveraging a simplified architecture to provide high-quality speech synthesis with minimal computational requirements. It integrates the LLaMa architecture, utilizes WavTokenizer, and can perform zero-shot voice cloning without complex adapters, distinguishing it from traditional TTS models.
Address: https://www.outeai.com/blog/OuteTTS-0.1-350M
