EP42 - HierSpeech++: Bridging the Gap between Semantic and Acoustic Representation of Speech by Hierarchical Variational Inference for Zero-shot Speech Synthesis

Download the paper - Read the paper on Hugging Face

Charlie: Hey everyone, I’m Charlie and alongside me is the brilliant Clio, a tech and AI wizard. Welcome to episode 42 of Paper Brief, where we dive into the intricacies of AI research papers. Today we’re exploring ‘HierSpeech++’, a fascinating development in zero-shot speech synthesis. Clio, what’s the scoop on this one?

Clio: Well, Charlie, HierSpeech++ is a leap forward in text-to-speech and voice conversion technology. It navigates past the slow speeds and fragility of previous systems, offering fast and robust speech synthesis.

Charlie: Sounds promising! How exactly does it improve on the past models?

Clio: It uses what’s called a hierarchical speech synthesis framework. By organizing data in hierarchical structures, it not only boosts the sturdiness and expressiveness but also drastically increases the naturalness and speaker likeness in the syntheses.

Charlie: Impressive, but how does it deal with different speakers’ voices? That must be challenging.

Clio: That’s where the ‘zero-shot’ aspect comes in. It can generate speech with human-level quality, capturing nuances of new speakers without needing extensive training data for each voice.

Charlie: Human-level quality is a bold claim! Can it back it up?

Clio: Absolutely. HierSpeech++ excels against other large language model-based systems and even diffusion-based models. They conducted numerous experiments to prove this.

Charlie: I’m curious about the technical details. How does it transform the text to speech?

Clio: It has this innovative component known as ’text-to-vec’, which forms a self-supervised speech representation and an F0 representation from the text, capturing the needed prosody.

Charlie: Prosody’s about rhythm and intonation, right? How important is that?

Clio: Quite crucial. It’s what makes speech sound natural, expressive, and easy to listen to. Their model can synthesize high-quality speech that feels real, even in ‘zero-shot’ scenarios.

Charlie: What about the output quality?

Clio: HierSpeech++ includes a speech super-resolution framework, scaling up from 16 kHz to a crystal-clear 48 kHz, similar to what you’d expect in high-quality music tracks.

Charlie: Amazing! This sounds like a game-changer for the industry. Any final thoughts?

Clio: For anyone keen to delve deeper or even tinker with HierSpeech++, the good news is that the audio samples and the source code are open for grabs online.