5 citations · 6 across the 12 of their papers we have counts for
5 papers · 1 filter
LatentSpeech: Latent Diffusion for Text-To-Speech Generation
Haowei Lou, Helen Paik, Pari Delir Haghighi +2
Diffusion-based Generative AI gains significant attention for its superior performance over other generative techniques like Generative Adversarial Networks and Variational Autoenc…
Aligner-Guided Training Paradigm: Advancing Text-to-Speech Models with Aligner Guided Duration
Haowei Lou, Helen Paik, Wen Hu +1
Recent advancements in text-to-speech (TTS) systems, such as FastSpeech and StyleSpeech, have significantly improved speech generation quality. However, these models often rely on…
LightLLM: A Versatile Large Language Model for Predictive Light Sensing
Jiawei Hu, Hong Jia, Mahbub Hassan +3
We propose LightLLM, a model that fine tunes pre-trained large language models (LLMs) for light-based sensing tasks. It integrates a sensor data encoder to extract key features, a…
Brain Network Diffusion-Driven fMRI Connectivity Augmentation for Enhanced Autism Spectrum Disorder Diagnosis
Haokai Zhao, Haowei Lou, Lina Yao +1
Functional magnetic resonance imaging (fMRI) is an emerging neuroimaging modality that is commonly modeled as networks of Regions of Interest (ROIs) and their connections, named fu…
StyleSpeech: Parameter-efficient Fine Tuning for Pre-trained Controllable Text-to-Speech
Haowei Lou, Helen Paik, Wen Hu +1
This paper introduces StyleSpeech, a novel Text-to-Speech~(TTS) system that enhances the naturalness and accuracy of synthesized speech. Building upon existing TTS technologies, St…