Sunday, May 25, 2025
LBNN
  • Business
  • Markets
  • Politics
  • Crypto
  • Finance
  • Energy
  • Technology
  • Taxes
  • Creator Economy
  • Wealth Management
  • Documentaries
No Result
View All Result
LBNN

A new model to produce more natural synthesized speech

Simon Osuji by Simon Osuji
May 27, 2024
in Artificial Intelligence
0
A new model to produce more natural synthesized speech
0
SHARES
1
VIEWS
Share on FacebookShare on Twitter


A new model to produce more natural synthesised speech
The proposed Diff-ETS framework for ETS. The deep blue blocks are trainable and the light blue block of the vocoder is frozen. ResBlock: Residual blocks, Attn: Attention, Conv: Convolutional layers. Credit: Ren et al

Recent technological advances are enabling the development of computational tools that could significantly improve the quality of life of individuals with disabilities or sensory impairments. These include so-called electromyography-to-speech (ETS) conversion models, designed to convert electrical signals produced by skeletal muscles into speech.

Related posts

15 Best Memorial Day Tech Deals (2025): iPads and Bluetooth Speakers

15 Best Memorial Day Tech Deals (2025): iPads and Bluetooth Speakers

May 24, 2025
Want to Claim the Solar Tax Credit? Get Installing Now

Want to Claim the Solar Tax Credit? Get Installing Now

May 24, 2025

Researchers at University of Bremen and SUPSI recently introduced Diff-ETS, a model for ETS conversion that could produce more natural synthesized speech. This model, introduced in a paper posted to the preprint server arXiv, could be used to develop new systems that allow people who are unable to speak, such as patients who underwent a laryngectomy (a surgery to remove part of the human voice box), to communicate with others.

Most previously introduced techniques for ETS conversion have two key components: an EMG encoder and a vocoder. The electromyography (EMG) encoder can convert EMG signals into acoustic speech features, while the vocoder uses these speech features to synthesize speech signals.

“Due to an inadequate amount of available data and noisy signals, the synthesized speech often exhibits a low level of naturalness,” Zhao Ren, Kevin Scheck and their colleagues wrote in their paper. “In this work, we propose Diff-ETS, an ETS model which uses a score-based diffusion probabilistic model to enhance the naturalness of synthesized speech. The diffusion model is applied to improve the quality of the acoustic features predicted by an EMG encoder.”

In contrast with many other ETS conversion models developed in the past, consisting of an encoder and vocoder, the researchers’ model has three components, namely an EMG encoder, a diffusion probabilistic model and a vocoder. The diffusion probabilistic model, the second of these components, is thus a new addition, which could result in more natural synthesized speech.

Ren, Scheck and their colleagues trained the EMG encoder to predict a so-called log Mel spectrogram (i.e., a visual representation of audio signals) and phoneme targets from EMG signals. The diffusion probabilistic model, on the other hand, was trained to enhance log Mel spectrograms, while the pre-trained vocoder can translate this spectrogram into synthesized speech.

The researchers evaluated the Diff-ETS model in a series of tests, comparing it with a baseline ETS technique. Their findings were highly promising, as the speech it synthesized was more natural and human-like than that produced by the baseline method.

“In our experiments, we evaluated fine-tuning the diffusion model on predictions of a pre-trained EMG encoder, and training both models in an end-to-end fashion,” Ren, Scheck and their colleagues wrote in their paper. “We compared Diff-ETS with a baseline ETS model without diffusion using objective metrics and a listening test. The results indicated the proposed Diff-ETS significantly improved speech naturalness over the baseline.”

In the future, the ETS conversion model developed by this team of researchers could be used to develop better technologies for the artificial generation of audible speech. These systems could allow people who are unable to speak to express their thoughts out loud, facilitating their interaction with others.

“In future efforts, one can reduce the number of model parameters using various methods, e. g., model compression and knowledge distillation, thereby generating speech samples in real-time,” the researchers wrote. “Moreover, a diffusion model can be trained together with the encoder and vocoder for further enhancing the speech quality.”

More information:
Zhao Ren et al, Diff-ETS: Learning a Diffusion Probabilistic Model for Electromyography-to-Speech Conversion, arXiv (2024). DOI: 10.48550/arxiv.2405.08021

Journal information:
arXiv

© 2024 Science X Network

Citation:
A new model to produce more natural synthesized speech (2024, May 27)
retrieved 27 May 2024
from https://techxplore.com/news/2024-05-natural-speech.html

This document is subject to copyright. Apart from any fair dealing for the purpose of private study or research, no
part may be reproduced without the written permission. The content is provided for information purposes only.





Source link

Previous Post

Iyo thinks its gen AI earbuds can succeed where Humane and Rabbit stumbled

Next Post

DSCT highlights contributions to maritime security and job creation

Next Post
DSCT highlights contributions to maritime security and job creation

DSCT highlights contributions to maritime security and job creation

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

RECOMMENDED NEWS

Meta’s Sheryl Sandberg to step down from board

Meta’s Sheryl Sandberg to step down from board

1 year ago
WTO members push to speed up Okonjo-Iweala’s second term bid as US election nears

WTO members push to speed up Okonjo-Iweala’s second term bid as US election nears

10 months ago
What it takes to innovate in the age of Gen AI

What it takes to innovate in the age of Gen AI

1 year ago
Dollar rally has HSBC flipping view, seeing gains through 2024

Dollar rally has HSBC flipping view, seeing gains through 2024

2 years ago

POPULAR NEWS

  • Ghana to build three oil refineries, five petrochemical plants in energy sector overhaul

    Ghana to build three oil refineries, five petrochemical plants in energy sector overhaul

    0 shares
    Share 0 Tweet 0
  • When Will SHIB Reach $1? Here’s What ChatGPT Says

    0 shares
    Share 0 Tweet 0
  • Matthew Slater, son of Jackson State great, happy to see HBCUs back at the forefront

    0 shares
    Share 0 Tweet 0
  • Dolly Varden Focuses on Adding Ounces the Remainder of 2023

    0 shares
    Share 0 Tweet 0
  • US Dollar Might Fall To 96-97 Range in March 2024

    0 shares
    Share 0 Tweet 0
  • Privacy Policy
  • Contact

© 2023 LBNN - All rights reserved.

No Result
View All Result
  • Home
  • Business
  • Politics
  • Markets
  • Crypto
  • Economics
    • Manufacturing
    • Real Estate
    • Infrastructure
  • Finance
  • Energy
  • Creator Economy
  • Wealth Management
  • Taxes
  • Telecoms
  • Military & Defense
  • Careers
  • Technology
  • Artificial Intelligence
  • Investigative journalism
  • Art & Culture
  • Documentaries
  • Quizzes
    • Enneagram quiz
  • Newsletters
    • LBNN Newsletter
    • Divergent Capitalist

© 2023 LBNN - All rights reserved.