Text-to-Speech (TTS) models are designed to convert written text into natural-sounding speech.
Purpose: TTS models generate synthetic speech from text input, aiming to produce natural-sounding audio that mimics human speech.
Applications:
Audiobook and podcast creation
Model Types:
High-definition models like TTS-1-HD for higher quality audio
Voice Options: Many TTS systems offer multiple voice options. For example, OpenAI's TTS API provides 6 built-in voices: alloy, echo, fable, onyx, nova, and shimmer.
Language Support: Advanced TTS models can support multiple languages. For instance, some models can handle over 50 languages, including English, Spanish, French, German, and many others.
Features:
Ability to adjust speech rate and pitch in some models
Popular TTS Models:
Suno's Bark: A prompt-based TTS model
Open-Source Options: There are numerous open-source TTS models and frameworks available, such as Mozilla's TTS project and the Coqui-AI TTS toolkit.
Evaluation Metrics: The quality of TTS models is often measured using metrics like Mel Cepstral Distortion (MCD).
Customization: Some TTS systems allow for fine-tuning or adaptation to specific voices or accents, though this capability varies between models.
TTS technology continues to evolve, with ongoing research focused on improving naturalness, expressiveness, and language support across various applications.