5 papers
FlowW2N: Whispered-to-Normal Speech Conversion via Flow-Matching
Fabian Ritter-Gutierrez, Md Asif Jalal, Pablo Peso Parada +5
Whispered-to-normal (W2N) speech conversion aims to reconstruct missing phonation from whispered input while preserving content and speaker identity. This task is challenging due t…
Robust Target Speaker Diarization and Separation via Augmented Speaker Embedding Sampling
Md Asif Jalal, Luca Remaggi, Vasileios Moschopoulos +7
Traditional speech separation and speaker diarization approaches rely on prior knowledge of target speakers or a predetermined number of participants in audio signals. To address t…
Diffusion based Text-to-Music Generation with Global and Local Text based Conditioning
Jisi Zhang, Pablo Peso Parada, Md Asif Jalal +1
Diffusion based Text-To-Music (TTM) models generate music corresponding to text descriptions. Typically UNet based diffusion models condition on text embeddings generated from a pr…
persoDA: Personalized Data Augmentation for Personalized ASR
Pablo Peso Parada, Spyros Fontalis, Md Asif Jalal +6
Data augmentation (DA) is ubiquitously used in training of Automatic Speech Recognition (ASR) models. DA offers increased data variability, robustness and generalization against di…
Exploring compressibility of transformer based text-to-music (TTM) models
Vasileios Moschopoulos, Thanasis Kotsiopoulos, Pablo Peso Parada +7
State-of-the art Text-To-Music (TTM) generative AI models are large and require desktop or server class compute, making them infeasible for deployment on mobile phones. This paper…