5 citations · 21 across the 13 of their papers we have counts for
4 papers · 2 filters
A Finetuned SpeechLLM for Joint Multi-Granular L2 Assessment and Natural-Language Rationales
Aditya Kamlesh Parikh, Cristian Tejedor-Garcia, Catia Cucchiarini +1
Automated L2 speech assessment can assign proficiency labels, but often lacks interpretability. We propose a rubric-guided SpeechLLM for multi-aspect, multi-granular assessment, tr…
Assessing Dutch Syllabification Algorithms and Improving Accuracy by Combining Phonetic and Orthographic Information through Deep Learning
Gus Lathouwers, Wieke Harmsen, Catia Cucchiarini +1
Syllabification describes the task of dividing words into syllables. Due to many rules and exceptions, training an algorithm to perform syllabification with high accuracy remains a…
Transcribing Children's Speech: ASR Performance and Obtaining Reliable Orthographic Transcriptions
Gus Lathouwers, Lingyun Gao, Catia Cucchiarini +1
Automatic speech recognition (ASR) has the potential to substantially reduce manual annotation effort in child speech research by generating automatic transcriptions. However, obta…
Rubric-Guided Fine-tuning of SpeechLLMs for Multi-Aspect, Multi-Rater L2 Reading-Speech Assessment
Aditya Kamlesh Parikh, Cristian Tejedor-Garcia, Catia Cucchiarini +1
Reliable and interpretable automated assessment of second-language (L2) speech remains a central challenge, as large speech-language models (SpeechLLMs) often struggle to align wit…