most citedInsights on Neural Representations for End-to-End Speech Recognition

6 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.SD2023

Empirical Interpretation of the Relationship Between Speech Acoustic Context and Emotion Recognition

Anna Ollerenshaw, Md Asif Jalal, Rosanna Milner +1

Speech emotion recognition (SER) is vital for obtaining emotional intelligence and understanding the contextual meaning of speech. Variations of consonant-vowel (CV) phonemic bound…

eess.AS2023

Towards domain generalisation in ASR with elitist sampling and ensemble knowledge distillation

Rehan Ahmad, Md Asif Jalal, Muhammad Umar Farooq +2

Knowledge distillation has widely been used for model compression and domain adaptation for speech applications. In the presence of multiple teachers, knowledge can easily be trans…

cs.CL2022★ 1 cited

Probing Statistical Representations For End-To-End ASR

Anna Ollerenshaw, Md Asif Jalal, Thomas Hain

End-to-End automatic speech recognition (ASR) models aim to learn a generalised speech representation to perform recognition. In this domain there is little research to analyse int…

cs.SD2022★ 1 cited

Dynamic Kernels and Channel Attention for Low Resource Speaker Verification

Anna Ollerenshaw, Md Asif Jalal, Thomas Hain

State-of-the-art speaker verification frameworks have typically focused on developing models with increasingly deeper (more layers) and wider (number of channels) models to improve…

cs.CL2022★ 6 cited

Insights on Neural Representations for End-to-End Speech Recognition

Anna Ollerenshaw, Md Asif Jalal, Thomas Hain

End-to-end automatic speech recognition (ASR) models aim to learn a generalised speech representation. However, there are limited tools available to understand the internal functio…