1 citations · 3 across the 7 of their papers we have counts for
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eess.AS2020
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…
eess.AS2020★ 1 cited
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…
eess.AS2020
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…