3 papers
eess.AS2026
BabyHuBERT: Multilingual Self-Supervised Learning for Segmenting Speakers in Child-Centered Long-Form Recordings
Théo Charlot, Tarek Kunze, Maxime Poli +3
Child-centered daylong recordings are essential for studying early language development, but existing speech models trained on clean adult data perform poorly due to acoustic and l…
eess.AS2025
Fifteen Years of Child-Centered Long-Form Recordings: Promises, Resources, and Remaining Challenges to Validity
Loann Peurey, Marvin Lavechin, Tarek Kunze +4
Audio-recordings collected with a child-worn device are a fundamental tool in child language research. Long-form recordings collected over whole days promise to capture children's…
eess.AS2025
Challenges in Automated Processing of Speech from Child Wearables: The Case of Voice Type Classifier
Tarek Kunze, Marianne Métais, Hadrien Titeux +5
Recordings gathered with child-worn devices promised to revolutionize both fundamental and applied speech sciences by allowing the effortless capture of children's naturalistic spe…