9 citations · 11 across the 6 of their papers we have counts for
8 papers
A Study on Bias and Fairness In Deep Speaker Recognition
Amirhossein Hajavi, Ali Etemad
With the ubiquity of smart devices that use speaker recognition (SR) systems as a means of authenticating individuals and personalizing their services, fairness of SR systems has b…
Audio Representation Learning by Distilling Video as Privileged Information
Amirhossein Hajavi, Ali Etemad
Deep audio representation learning using multi-modal audio-visual data often leads to a better performance compared to uni-modal approaches. However, in real-world scenarios both m…
Fine-grained Early Frequency Attention for Deep Speaker Recognition
Amirhossein Hajavi, Ali Etemad
Attention mechanisms have emerged as important tools that boost the performance of deep models by allowing them to focus on key parts of learned embeddings. However, current attent…
Siamese Capsule Network for End-to-End Speaker Recognition In The Wild
Amirhossein Hajavi, Ali Etemad
We propose an end-to-end deep model for speaker verification in the wild. Our model uses thin-ResNet for extracting speaker embeddings from utterances and a Siamese capsule network…
FluentNet: End-to-End Detection of Speech Disfluency with Deep Learning
Tedd Kourkounakis, Amirhossein Hajavi, Ali Etemad
Strong presentation skills are valuable and sought-after in workplace and classroom environments alike. Of the possible improvements to vocal presentations, disfluencies and stutte…
Fine-grained Early Frequency Attention for Deep Speaker Representation Learning
Amirhossein Hajavi, Ali Etemad
Deep learning techniques have considerably improved speech processing in recent years. Speaker representations extracted by deep learning models are being used in a wide range of t…