activity
20192026
most citedArtificial Intelligence Decision Support for Medical Triage

7 citations · 9 across the 5 of their papers we have counts for

collaborators

7 papers

cs.LG2026

Noise-Robust Forced Alignment for Spontaneous Speech

Laurin Wagner, Mario Zusag

We show that forced aligners degrade on spontaneous, noisy real-world speech, and that fillers, laughter, and disfluencies corrupt word boundaries, impacting many downstream applic…

cs.CL2026

Content is What Remains: Invariant Speech Tokenization from Parallel Utterances

Laurin Wagner, Bernhard Thallinger, Miroslav Stankovic +1

Discrete speech tokenizers aim to disentangle semantic from acoustic information, yet targets from self-supervised learning (SSL) models like HuBERT retain non-linguistic variation…

cs.CL2026

Transcription Policy as a Latent Variable: Activating Controllable Verbatim ASR with Word-Level Timing

Laurin Wagner, Mario Zusag, Bernhard Thallinger

Modern ASR models trained on heterogeneously annotated data treat transcription style (verbatim vs. intended) as an uncontrolled latent variable, causing measurable decoding instab…

cs.LG2024★ 2 cited

CrisperWhisper: Accurate Timestamps on Verbatim Speech Transcriptions

Laurin Wagner, Bernhard Thallinger, Mario Zusag

We demonstrate that carefully adjusting the tokenizer of the Whisper speech recognition model significantly improves the precision of word-level timestamps when applying dynamic ti…

cs.SD2023

Careful Whisper -- leveraging advances in automatic speech recognition for robust and interpretable aphasia subtype classification

Laurin Wagner, Mario Zusag, Theresa Bloder

This paper presents a fully automated approach for identifying speech anomalies from voice recordings to aid in the assessment of speech impairments. By combining Connectionist Tem…

cs.AI2020★ 7 cited

Artificial Intelligence Decision Support for Medical Triage

Chiara Marchiori, Douglas Dykeman, Ivan Girardi +6

Applying state-of-the-art machine learning and natural language processing on approximately one million of teleconsultation records, we developed a triage system, now certified and…

eess.IV2019

SAPSAM - Sparsely Annotated Pathological Sign Activation Maps - A novel approach to train Convolutional Neural Networks on lung CT scans using binary labels only

Mario Zusag, Sujal Desai, Marcello Di Paolo +3

Chronic Pulmonary Aspergillosis (CPA) is a complex lung disease caused by infection with Aspergillus. Computed tomography (CT) images are frequently requested in patients with susp…