350 citations · 652 across the 49 of their papers we have counts for
9 papers · 1 filter
Learn and Don't Forget: Adding a New Language to ASR Foundation Models
Mengjie Qian, Siyuan Tang, Rao Ma +2
Foundation ASR models often support many languages, e.g. 100 languages in Whisper. However, there has been limited work on integrating an additional, typically low-resource, langua…
Adapting an Unadaptable ASR System
Rao Ma, Mengjie Qian, Mark J. F. Gales +1
As speech recognition model sizes and training data requirements grow, it is increasingly common for systems to only be available via APIs from online service providers rather than…
Multi-Head State Space Model for Speech Recognition
Yassir Fathullah, Chunyang Wu, Yuan Shangguan +8
State space models (SSMs) have recently shown promising results on small-scale sequence and language modelling tasks, rivalling and outperforming many attention-based approaches. I…
Ensemble prosody prediction for expressive speech synthesis
Tian Huey Teh, Vivian Hu, Devang S Ram Mohan +7
Generating expressive speech with rich and varied prosody continues to be a challenge for Text-to-Speech. Most efforts have focused on sophisticated neural architectures intended t…
L2 proficiency assessment using self-supervised speech representations
Stefano Bannò, Kate M. Knill, Marco Matassoni +2
There has been a growing demand for automated spoken language assessment systems in recent years. A standard pipeline for this process is to start with a speech recognition system…
Confidence Estimation for Black Box Automatic Speech Recognition Systems Using Lattice Recurrent Neural Networks
Alexandros Kastanos, Anton Ragni, Mark Gales
Recently, there has been growth in providers of speech transcription services enabling others to leverage technology they would not normally be able to use. As a result, speech-ena…
Non-native Speaker Verification for Spoken Language Assessment
Linlin Wang, Yu Wang, Mark J. F. Gales
Automatic spoken language assessment systems are becoming more popular in order to handle increasing interests in second language learning. One challenge for these systems is to de…
Confidence Estimation and Deletion Prediction Using Bidirectional Recurrent Neural Networks
Anton Ragni, Qiujia Li, Mark Gales +1
The standard approach to assess reliability of automatic speech transcriptions is through the use of confidence scores. If accurate, these scores provide a flexible mechanism to fl…
Bi-Directional Lattice Recurrent Neural Networks for Confidence Estimation
Qiujia Li, Preben Ness, Anton Ragni +1
The standard approach to mitigate errors made by an automatic speech recognition system is to use confidence scores associated with each predicted word. In the simplest case, these…