collaborators

5 papers

cs.CL2025

Retrieval Augmented Generation based context discovery for ASR

Dimitrios Siskos, Stavros Papadopoulos, Pablo Peso Parada +3

This work investigates retrieval augmented generation as an efficient strategy for automatic context discovery in context-aware Automatic Speech Recognition (ASR) system, in order…

eess.AS2025

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…

eess.AS2024

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…

eess.AS2024

Locality enhanced dynamic biasing and sampling strategies for contextual ASR

Md Asif Jalal, Pablo Peso Parada, George Pavlidis +8

Automatic Speech Recognition (ASR) still face challenges when recognizing time-variant rare-phrases. Contextual biasing (CB) modules bias ASR model towards such contextually-releva…

eess.AS2024

Consistency Based Unsupervised Self-training For ASR Personalisation

Jisi Zhang, Vandana Rajan, Haaris Mehmood +7

On-device Automatic Speech Recognition (ASR) models trained on speech data of a large population might underperform for individuals unseen during training. This is due to a domain…