16 citations · 34 across the 11 of their papers we have counts for
11 papers
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…
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…
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…
Sound Tagging in Infant-centric Home Soundscapes
Mohammad Nur Hossain Khan, Jialu Li, Nancy L. McElwain +2
Certain environmental noises have been associated with negative developmental outcomes for infants and young children. Though classifying or tagging sound events in a domestic envi…
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…
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…
Towards Robust Family-Infant Audio Analysis Based on Unsupervised Pretraining of Wav2vec 2.0 on Large-Scale Unlabeled Family Audio
Jialu Li, Mark Hasegawa-Johnson, Nancy L. McElwain
To perform automatic family audio analysis, past studies have collected recordings using phone, video, or audio-only recording devices like LENA, investigated supervised learning m…
Visualizations of Complex Sequences of Family-Infant Vocalizations Using Bag-of-Audio-Words Approach Based on Wav2vec 2.0 Features
Jialu Li, Mark Hasegawa-Johnson, Nancy L. McElwain
In the U.S., approximately 15-17% of children 2-8 years of age are estimated to have at least one diagnosed mental, behavioral or developmental disorder. However, such disorders of…
Accent-Robust Automatic Speech Recognition Using Supervised and Unsupervised Wav2vec Embeddings
Jialu Li, Vimal Manohar, Pooja Chitkara +5
Speech recognition models often obtain degraded performance when tested on speech with unseen accents. Domain-adversarial training (DAT) and multi-task learning (MTL) are two commo…
Autosegmental Neural Nets: Should Phones and Tones be Synchronous or Asynchronous?
Jialu Li, Mark Hasegawa-Johnson
Phones, the segmental units of the International Phonetic Alphabet (IPA), are used for lexical distinctions in most human languages; Tones, the suprasegmental units of the IPA, are…
An Embodied, Platform-invariant Architecture for Connecting High-level Spatial Commands to Platform Articulation
A. Jang Sher, U. Huzaifa, J. Li +3
In contexts such as teleoperation, robot reprogramming, human-robot-interaction, and neural prosthetics, conveying movement commands to a robotic platform is often a limiting facto…