1 citations · 1 across the 7 of their papers we have counts for
8 papers
MICRO: Multi-Fidelity Active Search for Severe Error Discovery
Orlando Leone, Niclas Pokel, Pehuén Moure +2
Human feedback can vary in cost and informativeness. Strong feedback can reveal severe errors but is costly, so cheaper quality ratings can help decide which items to annotate. We…
When Audio-Language Models Fail to Leverage Multimodal Context for Dysarthric Speech Recognition
Pehuén Moure, Niclas Pokel, Bilal Bounajma +4
Automatic speech recognition (ASR) systems remain brittle on dysarthric and other atypical speech. Recent audio-language models raise the possibility of improving performance by co…
Demonstration of Adapt4Me: An Uncertainty-Aware Authoring Environment for Personalizing Automatic Speech Recognition to Non-normative Speech
Niclas Pokel, Yiming Zhao, Pehuén Moure +2
Personalizing Automatic Speech Recognition (ASR) for non-normative speech remains challenging because data collection is labor-intensive and model training is technically complex.…
Reasoning aligns language models to human cognition
Gonçalo Guiomar, Elia Torre, Pehuen Moure +4
Do language models make decisions under uncertainty like humans do, and what role does chain-of-thought (CoT) reasoning play in the underlying decision process? We introduce an act…
Variational Low-Rank Adaptation for Personalized Impaired Speech Recognition
Niclas Pokel, Pehuén Moure, Roman Boehringer +2
Speech impairments resulting from congenital disorders, such as cerebral palsy, down syndrome, or apert syndrome, as well as acquired brain injuries due to stroke, traumatic accide…
Data-Efficient ASR Personalization for Non-Normative Speech Using an Uncertainty-Based Phoneme Difficulty Score for Guided Sampling
Niclas Pokel, Pehuén Moure, Roman Böhringer +1
ASR systems struggle with non-normative speech due to high acoustic variability and data scarcity. We propose a data-efficient method using phoneme-level uncertainty to guide fine-…
Adapting Foundation Speech Recognition Models to Impaired Speech: A Semantic Re-chaining Approach for Personalization of German Speech
Niclas Pokel, Pehuén Moure, Roman Boehringer +1
Speech impairments caused by conditions such as cerebral palsy or genetic disorders pose significant challenges for automatic speech recognition (ASR) systems. Despite recent advan…
A Computational Design and Evaluation Tool for 3D Structures with Planar Surfaces
Chang Liu, Wenzhong Yan, Pehuen Moure +2
Three dimensional (3D) structures composed of planar surfaces can be build out of accessible materials using easier fabrication technique with shorter fabrication time. To better d…