1 citations · 3 across the 7 of their papers we have counts for
7 papers
Learning from human perception to improve automatic speaker verification in style-mismatched conditions
Amber Afshan, Abeer Alwan
Our prior experiments show that humans and machines seem to employ different approaches to speaker discrimination, especially in the presence of speaking style variability. The exp…
Attention-based conditioning methods using variable frame rate for style-robust speaker verification
Amber Afshan, Abeer Alwan
We propose an approach to extract speaker embeddings that are robust to speaking style variations in text-independent speaker verification. Typically, speaker embedding extraction…
Sequence-level Confidence Classifier for ASR Utterance Accuracy and Application to Acoustic Models
Amber Afshan, Kshitiz Kumar, Jian Wu
Scores from traditional confidence classifiers (CCs) in automatic speech recognition (ASR) systems lack universal interpretation and vary with updates to the underlying confidence…
Bi-APC: Bidirectional Autoregressive Predictive Coding for Unsupervised Pre-training and Its Application to Children's ASR
Ruchao Fan, Amber Afshan, Abeer Alwan
We present a bidirectional unsupervised model pre-training (UPT) method and apply it to children's automatic speech recognition (ASR). An obstacle to improving child ASR is the sca…
Speaker discrimination in humans and machines: Effects of speaking style variability
Amber Afshan, Jody Kreiman, Abeer Alwan
Does speaking style variation affect humans' ability to distinguish individuals from their voices? How do humans compare with automatic systems designed to discriminate between voi…
Variable frame rate-based data augmentation to handle speaking-style variability for automatic speaker verification
Amber Afshan, Jinxi Guo, Soo Jin Park +3
The effects of speaking-style variability on automatic speaker verification were investigated using the UCLA Speaker Variability database which comprises multiple speaking styles p…
Exploring the Use of an Unsupervised Autoregressive Model as a Shared Encoder for Text-Dependent Speaker Verification
Vijay Ravi, Ruchao Fan, Amber Afshan +2
In this paper, we propose a novel way of addressing text-dependent automatic speaker verification (TD-ASV) by using a shared-encoder with task-specific decoders. An autoregressive…