# EPG2S: Speech Generation and Speech Enhancement based on Electropalatography and Audio Signals using Multimodal Learning

arXiv: https://arxiv.org/abs/2206.07860 · HTML: https://mlsanity.com/paper/2206.07860/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 8 of its 39 references that are in the map.
- First posted on arXiv 16 Jun 2022.

## Builds on (most cited first, 8 of 8)

- [Parallel WaveGAN: A fast waveform generation model based on generative adversarial networks with multi-resolution spectrogram](https://mlsanity.com/paper/1910.11480/) (2019)
- [Audio-Visual Speech Enhancement Using Multimodal Deep Convolutional Neural Networks](https://mlsanity.com/paper/1709.00944/) (2017)
- [Lip2AudSpec: Speech reconstruction from silent lip movements video](https://mlsanity.com/paper/1710.09798/) (2017)
- [Digital Voicing of Silent Speech](https://mlsanity.com/paper/2010.02960/) (2020)
- [Lite Audio-Visual Speech Enhancement](https://mlsanity.com/paper/2005.11769/) (2020)
- [Improving Speaker-Independent Lipreading with Domain-Adversarial Training](https://mlsanity.com/paper/1708.01565/) (2017)
- [Time-Domain Multi-modal Bone/air Conducted Speech Enhancement](https://mlsanity.com/paper/1911.09847/) (2019)
- [EMA2S: An End-to-End Multimodal Articulatory-to-Speech System](https://mlsanity.com/paper/2102.03786/) (2021)

## Built on by (most cited first, 1 of 1)

- [SCGG: A Deep Structure-Conditioned Graph Generative Model](https://mlsanity.com/paper/2209.09681/) (2022)

## Abstract (arXiv)

Speech generation and enhancement based on articulatory movements facilitate communication when the scope of verbal communication is absent, e.g., in patients who have lost the ability to speak. Although various techniques have been proposed to this end, electropalatography (EPG), which is a monitoring technique that records contact between the tongue and hard palate during speech, has not been adequately explored. Herein, we propose a novel multimodal EPG-to-speech (EPG2S) system that utilizes EPG and speech signals for speech generation and enhancement. Different fusion strategies based on multiple combinations of EPG and noisy speech signals are examined, and the viability of the proposed method is investigated. Experimental results indicate that EPG2S achieves desirable speech generation outcomes based solely on EPG signals. Further, the addition of noisy speech signals is observed to improve quality and intelligibility. Additionally, EPG2S is observed to achieve high-quality speech enhancement based solely on audio signals, with the addition of EPG signals further improving the performance. The late fusion strategy is deemed to be the most effective approach for simultaneous speech generation and enhancement.