most citedBona fide Cross Testing Reveals Weak Spot in Audio Deepfake Detection Systems

2 citations · 3 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD20252 cited

Bona fide Cross Testing Reveals Weak Spot in Audio Deepfake Detection Systems

Chin Yuen Kwok, Jia Qi Yip, Zhen Qiu +2

Audio deepfake detection (ADD) models are commonly evaluated using datasets that combine multiple synthesizers, with performance reported as a single Equal Error Rate (EER). Howeve…

cs.CL2025

Improving Synthetic Data Training for Contextual Biasing Models with a Keyword-Aware Cost Function

Chin Yuen Kwok, Jia Qi Yip, Eng Siong Chng

Rare word recognition can be improved by adapting ASR models to synthetic data that includes these words. Further improvements can be achieved through contextual biasing, which tra…

cs.CL2025

Efficient Trie-based Biasing using K-step Prediction for Rare Word Recognition

Chin Yuen Kwok, Jia Qi yip

Contextual biasing improves rare word recognition of ASR models by prioritizing the output of rare words during decoding. A common approach is Trie-based biasing, which gives "bonu…

cs.CL2025

Continual Learning with Embedding Layer Surgery and Task-wise Beam Search using Whisper

Chin Yuen Kwok, Jia Qi Yip, Eng Siong Chng

Current Multilingual ASR models only support a fraction of the world's languages. Continual Learning (CL) aims to tackle this problem by adding new languages to pre-trained models…

eess.AS20241 cited

Speech Separation using Neural Audio Codecs with Embedding Loss

Jia Qi Yip, Chin Yuen Kwok, Bin Ma +1

Neural audio codecs have revolutionized audio processing by enabling speech tasks to be performed on highly compressed representations. Recent work has shown that speech separation…