4 papers
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…
Zero-Shot Speech LLMs for Multi-Aspect Evaluation of L2 Speech: Challenges and Opportunities
Aditya Kamlesh Parikh, Cristian Tejedor-Garcia, Catia Cucchiarini +1
An accurate assessment of L2 English pronunciation is crucial for language learning, as it provides personalized feedback and ensures a fair evaluation of individual progress. Howe…
Evaluating Logit-Based GOP Scores for Mispronunciation Detection
Aditya Kamlesh Parikh, Cristian Tejedor-Garcia, Catia Cucchiarini +1
Pronunciation assessment relies on goodness of pronunciation (GOP) scores, traditionally derived from softmax-based posterior probabilities. However, posterior probabilities may su…
Enhancing GOP in CTC-Based Mispronunciation Detection with Phonological Knowledge
Aditya Kamlesh Parikh, Cristian Tejedor-Garcia, Catia Cucchiarini +1
Computer-Assisted Pronunciation Training (CAPT) systems employ automatic measures of pronunciation quality, such as the goodness of pronunciation (GOP) metric. GOP relies on forced…