32 citations · 62 across the 16 of their papers we have counts for
16 papers
Mind the Shift: Using Delta SSL Embeddings to Enhance Child ASR
Zilai Wang, Natarajan Balaji Shankar, Kaiyuan Zhang +2
Self-supervised learning (SSL) models have achieved impressive results across many speech tasks, yet child automatic speech recognition (ASR) remains challenging due to limited dat…
Comparing Unsupervised and Supervised Semantic Speech Tokens: A Case Study of Child ASR
Mohan Shi, Natarajan Balaji Shankar, Kaiyuan Zhang +2
Discrete speech tokens have gained attention for their storage efficiency and integration with Large Language Models (LLMs). They are commonly categorized into acoustic and semanti…
Benchmarking Training Paradigms, Dataset Composition, and Model Scaling for Child ASR in ESPnet
Anyu Ying, Natarajan Balaji Shankar, Chyi-Jiunn Lin +7
Despite advancements in ASR, child speech recognition remains challenging due to acoustic variability and limited annotated data. While fine-tuning adult ASR models on child speech…
An Age-Agnostic System for Robust Speaker Verification
Jiusi Zheng, Vishwas Shetty, Natarajan Balaji Shankar +1
In speaker verification (SV), the acoustic mismatch between children's and adults' speech leads to suboptimal performance when adult-trained SV systems are applied to children's sp…
CHSER: A Dataset and Case Study on Generative Speech Error Correction for Child ASR
Natarajan Balaji Shankar, Zilai Wang, Kaiyuan Zhang +2
Automatic Speech Recognition (ASR) systems struggle with child speech due to its distinct acoustic and linguistic variability and limited availability of child speech datasets, lea…
Enhancing Age-Related Robustness in Children Speaker Verification
Vishwas M. Shetty, Jiusi Zheng, Steven M. Lulich +1
One of the main challenges in children's speaker verification (C-SV) is the significant change in children's voices as they grow. In this paper, we propose two approaches to improv…
Selective Attention Merging for low resource tasks: A case study of Child ASR
Natarajan Balaji Shankar, Zilai Wang, Eray Eren +1
While Speech Foundation Models (SFMs) excel in various speech tasks, their performance for low-resource tasks such as child Automatic Speech Recognition (ASR) is hampered by limite…
SOA: Reducing Domain Mismatch in SSL Pipeline by Speech Only Adaptation for Low Resource ASR
Natarajan Balaji Shankar, Ruchao Fan, Abeer Alwan
Recently, speech foundation models have gained popularity due to their superiority in finetuning downstream ASR tasks. However, models finetuned on certain domains, such as LibriSp…
Benchmarking Children's ASR with Supervised and Self-supervised Speech Foundation Models
Ruchao Fan, Natarajan Balaji Shankar, Abeer Alwan
Speech foundation models (SFMs) have achieved state-of-the-art results for various speech tasks in supervised (e.g. Whisper) or self-supervised systems (e.g. WavLM). However, the p…
UniEnc-CASSNAT: An Encoder-only Non-autoregressive ASR for Speech SSL Models
Ruchao Fan, Natarajan Balaji Shanka, Abeer Alwan
Non-autoregressive automatic speech recognition (NASR) models have gained attention due to their parallelism and fast inference. The encoder-based NASR, e.g. connectionist temporal…
Non-uniform Speaker Disentanglement For Depression Detection From Raw Speech Signals
Jinhan Wang, Vijay Ravi, Abeer Alwan
While speech-based depression detection methods that use speaker-identity features, such as speaker embeddings, are popular, they often compromise patient privacy. To address this…
A CTC Alignment-based Non-autoregressive Transformer for End-to-end Automatic Speech Recognition
Ruchao Fan, Wei Chu, Peng Chang +1
Recently, end-to-end models have been widely used in automatic speech recognition (ASR) systems. Two of the most representative approaches are connectionist temporal classification…
A Step Towards Preserving Speakers' Identity While Detecting Depression Via Speaker Disentanglement
Vijay Ravi, Jinhan Wang, Jonathan Flint +1
Preserving a patient's identity is a challenge for automatic, speech-based diagnosis of mental health disorders. In this paper, we address this issue by proposing adversarial disen…
Unsupervised Instance Discriminative Learning for Depression Detection from Speech Signals
Jinhan Wang, Vijay Ravi, Jonathan Flint +1
Major Depressive Disorder (MDD) is a severe illness that affects millions of people, and it is critical to diagnose this disorder as early as possible. Detecting depression from vo…
Automatic Dialect Density Estimation for African American English
Alexander Johnson, Kevin Everson, Vijay Ravi +3
In this paper, we explore automatic prediction of dialect density of the African American English (AAE) dialect, where dialect density is defined as the percentage of words in an u…
Can Social Robots Effectively Elicit Curiosity in STEM Topics from K-1 Students During Oral Assessments?
Alexander Johnson, Alejandra Martin, Marlen Quintero +2
This paper presents the results of a pilot study that introduces social robots into kindergarten and first-grade classroom tasks. This study aims to understand 1) how effective soc…