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20242026
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eess.AS2026

Robust Multi-Tier Infant-Centered Audio Understanding with Whisper via Structured Speaker Conditioning

Xulin Fan, Jialu Li, Mohammad Nur Hossain Khan +4

Recent advances in model design and self-supervised audio representations have improved speech and audio understanding, yet infant-centered naturalistic recordings remain challengi…

eess.AS2026

Age-Aware Adapter Tuning for Children's Speech Recognition

Jialu Li

Children's automatic speech recognition (ASR) remains challenging because child speech differs from adult speech and varies substantially across developmental stages. While adapter…

eess.AS2025

Automated Analysis of Naturalistic Recordings in Early Childhood: Applications, Challenges, and Opportunities

Jialu Li, Marvin Lavechin, Xulin Fan +4

Naturalistic recordings capture audio in real-world environments where participants behave naturally without interference from researchers or experimental protocols. Naturalistic l…

eess.AS2024

Analysis of Self-Supervised Speech Models on Children's Speech and Infant Vocalizations

Jialu Li, Mark Hasegawa-Johnson, Nancy L. McElwain

To understand why self-supervised learning (SSL) models have empirically achieved strong performances on several speech-processing downstream tasks, numerous studies have focused o…

eess.AS2024

Enhancing Child Vocalization Classification with Phonetically-Tuned Embeddings for Assisting Autism Diagnosis

Jialu Li, Mark Hasegawa-Johnson, Karrie Karahalios

The assessment of children at risk of autism typically involves a clinician observing, taking notes, and rating children's behaviors. A machine learning model that can label adult…