Search Results for author:
Found 5 papers, 0 papers with code
LatentColorization: Latent Diffusion-Based Speaker Video Colorization
While current research predominantly focuses on image-based colorization, the domain of video-based colorization remains relatively unexplored.
Synthetic Speaking Children -- Why We Need Them and How to Make Them
Contemporary Human Computer Interaction (HCI) research relies primarily on neural network models for machine vision and speech understanding of a system user.
Speech Driven Video Editing via an Audio-Conditioned Diffusion Model
Taking inspiration from recent developments in visual generative tasks using diffusion models, we propose a method for end-to-end speech-driven video editing using a denoising diffusion model.
A Wav2vec2-Based Experimental Study on Self-Supervised Learning Methods to Improve Child Speech Recognition
Our models outperformed the wav2vec2 BASE 960 on child speech which is considered a state-of-the-art ASR model on adult speech by just using 10 hours of child speech data in finetuning.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
A Text-to-Speech Pipeline, Evaluation Methodology, and Initial Fine-Tuning Results for Child Speech Synthesis
Speech synthesis has come a long way as current text-to-speech (TTS) models can now generate natural human-sounding speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
