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"What is the top Text-to-Speech model for generating high-quality audio books as of now?"

Currently, the top TTS model for audiobooks is Google's WaveNet, which uses a neural network to generate high-quality audio that is comparable to human recordings.

WaveNet uses a technique called "end-to-end" learning, where the model learns to generate audio waves directly from text input, without the need for intermediate representations.

The WaveNet model is trained on a massive dataset of over 10,000 hours of audio, which allows it to learn the patterns and nuances of human speech.

Another popular TTS model is Amazon's Polly, which uses a deep learning-based approach to generate high-quality speech synthesis.

Polly uses a technique called "concatenative synthesis," where the model concatenates small units of recorded speech to generate new audio samples.

The quality of TTS models has improved significantly in recent years, with some models achieving a mean opinion score (MOS) of over 4.5, which is comparable to human recordings.

The MOS is a subjective measure of audio quality, where listeners rate the quality of the audio on a scale of 1-5.

The TTS Arena benchmark, developed by Hugging Face, allows users to compare different TTS models side-by-side and vote on which model is best.

The top-ranked model on the TTS Arena leaderboard is Google's WaveNet, followed closely by Amazon's Polly.

The NaturalReader TTS model, developed by NaturalSoft, offers a rich selection of human voice options in multiple languages and accents.

The MaryTTS model, developed by the German Research Center for Artificial Intelligence, is a flexible and modular architecture for building TTS systems.

The eSpeak.ng model, developed by the Open Source TTS project, is a compact and open-source TTS engine that is highly customizable.

The eSpeak.ng model uses a technique called "statistical parametric synthesis," which models the probability distribution of audio frames to generate new audio samples.

The FestVocal model, developed by Carnegie Mellon University, uses a technique called "unit selection synthesis," where the model concatenates small units of recorded speech to generate new audio samples.

The highest-rated TTS model on the TTS Arena leaderboard, Google's WaveNet, has an MOS of 4.64, which is comparable to human recordings.

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