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eess.AS20261 cited

Speech Quality-Based Localization of Low-Quality Speech and Text-to-Speech Synthesis Artefacts

Michael Kuhlmann, Alexander Werning, Thilo von Neumann +1

A large number of works view the automatic assessment of speech from an utterance- or system-level perspective. While such approaches are good in judging overall quality, they cann…

eess.AS2026

On the Role of Spatial Features in Foundation-Model-Based Speaker Diarization

Marc Deegen, Tobias Gburrek, Tobias Cord-Landwehr +4

Recent advances in speaker diarization exploit large pretrained foundation models, such as WavLM, to achieve state-of-the-art performance on multiple datasets. Systems like DiariZe…

eess.AS2025

Error Analysis in a Modular Meeting Transcription System

Peter Vieting, Simon Berger, Thilo von Neumann +3

Meeting transcription is a field of high relevance and remarkable progress in recent years. Still, challenges remain that limit its performance. In this work, we extend a previousl…

eess.AS2025

Combining TF-GridNet and Mixture Encoder for Continuous Speech Separation for Meeting Transcription

Peter Vieting, Simon Berger, Thilo von Neumann +3

Many real-life applications of automatic speech recognition (ASR) require processing of overlapped speech. A common method involves first separating the speech into overlap-free st…

eess.AS2024

Meeting Recognition with Continuous Speech Separation and Transcription-Supported Diarization

Thilo von Neumann, Christoph Boeddeker, Tobias Cord-Landwehr +2

We propose a modular pipeline for the single-channel separation, recognition, and diarization of meeting-style recordings and evaluate it on the Libri-CSS dataset. Using a Continuo…