2 citations · 5 across the 7 of their papers we have counts for
9 papers
Fundamental Frequency Feature Normalization and Data Augmentation for Child Speech Recognition
Gary Yeung, Ruchao Fan, Abeer Alwan
Automatic speech recognition (ASR) systems for young children are needed due to the importance of age-appropriate educational technology. Because of the lack of publicly available…
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…
Analysis of Disfluency in Children's Speech
Trang Tran, Morgan Tinkler, Gary Yeung +2
Disfluencies are prevalent in spontaneous speech, as shown in many studies of adult speech. Less is understood about children's speech, especially in pre-school children who are st…
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…