Speech Synthesis News and Research

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SALAD Model Redefines Text-to-Speech with Continuous Diffusion

Researchers introduce SALAD, a zero-shot text-to-speech model leveraging continuous diffusion to enhance speech quality, intelligibility, and speaker similarity in audio synthesis.

3 Nov 2024

Deep Learning and Bayesian Regularization for Urban Planning

Researchers from South Korea and China present a pioneering approach in Scientific Reports, showcasing how deep learning techniques, coupled with Bayesian regularization and graphical analysis, revolutionize urban planning and smart city development. By integrating advanced computational methods, their study offers insights into traffic prediction, urban infrastructure optimization, data privacy, and safety and security, paving the way for more efficient, sustainable, and livable urban environments.

8 Mar 2024

GANs Revolutionize Spatial Computing in Design Fields

Delve into the realm of spatial computing design with the groundbreaking application of Generative Adversarial Networks (GANs), as presented in Scientific Reports. By introducing an innovative icon generation method and incorporating interactive design features, researchers have paved the way for enhanced efficiency and creativity in various design domains, including architecture, interior design, urban planning, and landscape design.

7 Mar 2024

Flash Attention Generative Adversarial Network for Enhanced Lip-to-Speech Technology

Researchers introduced the Flash Attention Generative Adversarial Network (FA-GAN) to address challenges in Chinese sentence-level lip-to-speech (LTS) synthesis. FA-GAN, incorporating joint modeling of global and local lip movements, outperformed existing models in both English and Chinese datasets, showcasing superior performance in speech quality metrics like STOI and ESTOI.

4 Mar 2024

PHEME: Transforming Speech Synthesis with Efficiency and Quality

Researchers unveil the PHEME model series, introducing a breakthrough in speech generation. PHEME's efficient design, leveraging modularized encoding and non-autoregressive decoding, achieves near-human speech synthesis, providing a scalable solution that bridges the gap between quality and resource efficiency. This model not only outperforms counterparts like VALL-E and SoundStorm but also demonstrates the potential to revolutionize applications with its production-friendly and highly effective approach.

11 Jan 2024

RVTALL: Advancing Speech Recognition with Multimodal Dataset

Researchers unveil RVTALL, a groundbreaking multimodal dataset for contactless speech recognition. Integrating data from UWB and mmWave radars, depth cameras, lasers, and audio-visual sources, the dataset aids in exploring non-invasive speech analysis. The study demonstrates applications in silent speech recognition, speech enhancement, analysis, and synthesis, though it acknowledges limitations in sample size and diversity. The dataset stands as a robust tool for advancing research in speech-related technologies.

19 Dec 2023

Advancing Linguistic E-Learning with AI Innovations

Researchers have expanded an e-learning system for phonetic transcription with three AI-driven enhancements. These improvements include a speech classification module, a multilingual word-to-IPA converter, and an IPA-to-speech synthesis system, collectively enhancing linguistic education and phonetic transcription capabilities in e-learning environments.

29 Sep 2023

Expresso: A Benchmark and Analysis of Discrete Expressive Speech Resynthesis

Researchers from Meta AI introduce EXPRESSO, a high-quality dataset of expressive speech and a benchmark for discrete textless speech resynthesis. This dataset, comprising diverse vocal expressions like emotions, accents, and non-verbal sounds, along with a resynthesis challenge, advances the capabilities of speech synthesis systems, enabling them to capture a wide range of expressive styles.

24 Sep 2023

SeamlessM4T: Advancing Multilingual Speech Translation

Meta AI researchers introduce SeamlessM4T, a versatile model supporting speech-to-speech, text-to-speech, and text-to-text translation for 100 languages. Leveraging vast audio data and innovative techniques, SeamlessM4T outperforms previous models, promising enhanced translation quality, language coverage, and responsible AI practices.

22 Sep 2023

Unlocking Clear Communication: D2StarGAN for Speech Intelligibility Enhancement

Researchers explore the innovative D2StarGAN model, a cutting-edge deep learning solution designed to enhance speech intelligibility in noisy environments. They also discuss how this framework leverages dual non-parallel speech style conversion techniques to create natural and clear speech, revolutionizing communication in challenging auditory conditions.

29 Aug 2023