Quantization-aware training with ternary weights plus base-3 weight indexing reduces a JETS/HiFi-GAN TTS model from 25.66 MB to 4.39 MB while keeping naturalness MOS around 3.1 to 3.3.
Additionally, we introduced a method called weight indexing to further re- duce model size
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BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing
Quantization-aware training with ternary weights plus base-3 weight indexing reduces a JETS/HiFi-GAN TTS model from 25.66 MB to 4.39 MB while keeping naturalness MOS around 3.1 to 3.3.