activity
20202025
collaborators

7 papers

eess.AS2025

ValSub: Subsampling Validation Data to Mitigate Forgetting during ASR Personalization

Haaris Mehmood, Karthikeyan Saravanan, Pablo Peso Parada +5

Automatic Speech Recognition (ASR) is widely used within consumer devices such as mobile phones. Recently, personalization or on-device model fine-tuning has shown that adaptation…

eess.AS2025

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…

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…

eess.AS2023

On-Device Speaker Anonymization of Acoustic Embeddings for ASR based onFlexible Location Gradient Reversal Layer

Md Asif Jalal, Pablo Peso Parada, Jisi Zhang +5

Smart devices serviced by large-scale AI models necessitates user data transfer to the cloud for inference. For speech applications, this means transferring private user informatio…

eess.AS2020

Adaptable Multi-Domain Language Model for Transformer ASR

Taewoo Lee, Min-Joong Lee, Tae Gyoon Kang +10

We propose an adapter based multi-domain Transformer based language model (LM) for Transformer ASR. The model consists of a big size common LM and small size adapters. The model ca…