activity
20232026
most citedAlzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses

14 citations · 35 across the 14 of their papers we have counts for

collaborators

14 papers

cs.CL2026

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…

cs.CL2026

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…

cs.CL2026

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…

eess.AS2026

Utterance-Level Methods for Identifying Reliable ASR-Output for Child Speech

Gus Lathouwers, Lingyun Gao, Catia Cucchiarini +1

Automatic Speech Recognition (ASR) is increasingly used in applications involving child speech, such as language learning and literacy acquisition. However, the effectiveness of su…

cs.CL2026

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…

eess.AS2026

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…

eess.AS2025★ 4 cited

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…

eess.AS2025★ 1 cited

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…

eess.AS2025★ 2 cited

Improving Child Speech Recognition and Reading Mistake Detection by Using Prompts

Lingyun Gao, Cristian Tejedor-Garcia, Catia Cucchiarini +1

Automatic reading aloud evaluation can provide valuable support to teachers by enabling more efficient scoring of reading exercises. However, research on reading evaluation systems…

cs.CL2024★ 4 cited

Reading Miscue Detection in Primary School through Automatic Speech Recognition

Lingyun Gao, Cristian Tejedor-Garcia, Helmer Strik +1

Automatic reading diagnosis systems can benefit both teachers for more efficient scoring of reading exercises and students for accessing reading exercises with feedback more easily…

cs.CL2023★ 1 cited

Automatic Speech Recognition of Non-Native Child Speech for Language Learning Applications

Simone Wills, Yu Bai, Cristian Tejedor-Garcia +2

Voicebots have provided a new avenue for supporting the development of language skills, particularly within the context of second language learning. Voicebots, though, have largely…

cs.CL2023★ 5 cited

An ASR-Based Tutor for Learning to Read: How to Optimize Feedback to First Graders

Yu Bai, Cristian Tejedor-Garcia, Ferdy Hubers +2

The interest in employing automatic speech recognition (ASR) in applications for reading practice has been growing in recent years. In a previous study, we presented an ASR-based D…

cs.CL2023★ 4 cited

Automatic Assessment of Oral Reading Accuracy for Reading Diagnostics

Bo Molenaar, Cristian Tejedor-Garcia, Helmer Strik +1

Automatic assessment of reading fluency using automatic speech recognition (ASR) holds great potential for early detection of reading difficulties and subsequent timely interventio…

cs.CL2023★ 14 cited

Alzheimer Disease Classification through ASR-based Transcriptions: Exploring the Impact of Punctuation and Pauses

Lucía Gómez-Zaragozá, Simone Wills, Cristian Tejedor-Garcia +3

Alzheimer's Disease (AD) is the world's leading neurodegenerative disease, which often results in communication difficulties. Analysing speech can serve as a diagnostic tool for id…