55 citations · 65 across the 14 of their papers we have counts for
15 papers
ART-NAD: An Articulatory Inversion-based Neural Acoustic Distance for Pathological Speech Intelligibility Assessment
Bence Mark Halpern, Thomas Tienkamp, Defne Abur +1
Speech assessment tools for speakers with speech pathology must be both accurate and interpretable if they are to be adopted in clinical practice. Existing reference-audio measures…
Improving Automatic Speech Recognition for Speakers Treated for Oral Cancer using Data Augmentation and LLM Error Correction
Hidde Folkertsma, Thomas Tienkamp, Sebastiaan de Visscher +4
In recent years, the performance of automatic speech recognition (ASR) systems has made considerable progress. Unfortunately, for people with speech impairments, such as people tre…
PathBench: Speech Intelligibility Benchmark for Automatic Pathological Speech Assessment
Bence Mark Halpern, Thomas Tienkamp, Defne Abur +1
Automatic speech intelligibility assessment is crucial for monitoring speech disorders and therapy efficacy. However, existing methods are difficult to compare: research is fragmen…
Towards explainable reference-free speech intelligibility evaluation of people with pathological speech
Bence Mark Halpern, Thomas Tienkamp, Defne Abur +1
Objective assessment of speech that reflects meaningful changes in communication is crucial for clinical decision making and reproducible research. While existing objective assessm…
XPPG-PCA: Reference-free automatic speech severity evaluation with principal components
Bence Mark Halpern, Thomas B. Tienkamp, Teja Rebernik +5
Reliably evaluating the severity of a speech pathology is crucial in healthcare. However, the current reliance on expert evaluations by speech-language pathologists presents severa…
Reference-free automatic speech severity evaluation using acoustic unit language modelling
Bence Mark Halpern, Tomoki Toda
Speech severity evaluation is becoming increasingly important as the economic burden of speech disorders grows. Current speech severity models often struggle with generalization, l…
Relationship between objective and subjective perceptual measures of speech in individuals with head and neck cancer
Bence Mark Halpern, Thomas Tienkamp, Teja Rebernik +4
Meaningful speech assessment is vital in clinical phonetics and therapy monitoring. This study examined the link between perceptual speech assessments and objective acoustic measur…
Quantifying the effect of speech pathology on automatic and human speaker verification
Bence Mark Halpern, Thomas Tienkamp, Wen-Chin Huang +7
This study investigates how surgical intervention for speech pathology (specifically, as a result of oral cancer surgery) impacts the performance of an automatic speaker verificati…
Improving severity preservation of healthy-to-pathological voice conversion with global style tokens
Bence Mark Halpern, Wen-Chin Huang, Lester Phillip Violeta +2
In healthy-to-pathological voice conversion (H2P-VC), healthy speech is converted into pathological while preserving the identity. The paper improves on previous two-stage approach…
Manipulation of oral cancer speech using neural articulatory synthesis
Bence Mark Halpern, Teja Rebernik, Thomas Tienkamp +5
We present an articulatory synthesis framework for the synthesis and manipulation of oral cancer speech for clinical decision making and alleviation of patient stress. Objective an…
The Effectiveness of Time Stretching for Enhancing Dysarthric Speech for Improved Dysarthric Speech Recognition
Luke Prananta, Bence Mark Halpern, Siyuan Feng +1
In this paper, we investigate several existing and a new state-of-the-art generative adversarial network-based (GAN) voice conversion method for enhancing dysarthric speech for imp…
Towards Identity Preserving Normal to Dysarthric Voice Conversion
Wen-Chin Huang, Bence Mark Halpern, Lester Phillip Violeta +2
We present a voice conversion framework that converts normal speech into dysarthric speech while preserving the speaker identity. Such a framework is essential for (1) clinical dec…
An Objective Evaluation Framework for Pathological Speech Synthesis
Bence Mark Halpern, Julian Fritsch, Enno Hermann +3
The development of pathological speech systems is currently hindered by the lack of a standardised objective evaluation framework. In this work, (1) we utilise existing detection a…
Pathological voice adaptation with autoencoder-based voice conversion
Marc Illa, Bence Mark Halpern, Rob van Son +2
In this paper, we propose a new approach to pathological speech synthesis. Instead of using healthy speech as a source, we customise an existing pathological speech sample to a new…
Quantifying Bias in Automatic Speech Recognition
Siyuan Feng, Olya Kudina, Bence Mark Halpern +1
Automatic speech recognition (ASR) systems promise to deliver objective interpretation of human speech. Practice and recent evidence suggests that the state-of-the-art (SotA) ASRs…