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In the digital age, Text-to-Speech (TTS) technology has become a part of our daily lives. Whether it’s smart assistants, voice navigation, or accessibility services, high-quality speech synthesis technology continuously enhances our user experience. Today, I want to introduce an exciting open-source project—Parler-TTS, launched by Hugging Face, which aims to provide a new, high-quality speech synthesis solution.
Parler-TTS is a lightweight TTS model, which can generate natural-sounding speech based on the given speaker style. This means that through Parler-TTS, we can customize features such as voice gender, pitch, and speaking style, creating more personalized and realistic speech outputs.
Unlike other TTS models, the open-source nature of Parler-TTS is its biggest highlight. All datasets, preprocessing steps, training code, and model weights are publicly released and licensed under a permissive license, allowing the developer community to freely use, modify, and extend these resources to advance TTS technology.
Currently, Parler-TTS has released its first model with 600M parameters, trained on 10.5K hours of audio data. The development team plans to expand to 50k hours of data in the coming weeks to prepare for the upcoming v1 model. This indicates that Parler-TTS will have significant improvements in quality and performance.
As an open-source project, Parler-TTS not only provides a powerful tool for the developer community but also opens up new possibilities for the future development of TTS technology. Let’s look forward to Parler-TTS’s performance in the future and explore its potential in various application scenarios.
Project link: https://github.com/huggingface/parler-tts
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