activity
20212026
most citedSpatio-spectral diarization of meetings by combining TDOA-based segmentation and speaker embedding-based clustering

4 citations · 13 across the 15 of their papers we have counts for

collaborators

15 papers

eess.AS2026

Speech Quality Embeddings for Improved Detection and Classification of Degradations in Speech Signals

Michael Kuhlmann, Tobias Cord-Landwehr, Reinhold Haeb-Umbach

Automatic subjective speech quality assessment (SSQA) traditionally estimates speech quality on an utterance or system level. While this resolution was adequate for older transmiss…

eess.AS2026

Loose coupling of spectral and spatial models for multi-channel diarization and enhancement of meetings in dynamic environments

Adrian Meise, Tobias Cord-Landwehr, Christoph Boeddeker +3

Sound capture by microphone arrays opens the possibility to exploit spatial, in addition to spectral, information for diarization and signal enhancement, two important tasks in mee…

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

On the Application of Diffusion Models for Simultaneous Denoising and Dereverberation

Adrian Meise, Tobias Cord-Landwehr, Reinhold Haeb-Umbach

Diffusion models have been shown to achieve natural-sounding enhancement of speech degraded by noise or reverberation. However, their simultaneous denoising and dereverberation cap…

eess.AS2025★ 4 cited

Spatio-spectral diarization of meetings by combining TDOA-based segmentation and speaker embedding-based clustering

Tobias Cord-Landwehr, Tobias Gburrek, Marc Deegen +1

We propose a spatio-spectral, combined model-based and data-driven diarization pipeline consisting of TDOA-based segmentation followed by embedding-based clustering. The proposed s…

eess.AS2024

Simultaneous Diarization and Separation of Meetings through the Integration of Statistical Mixture Models

Tobias Cord-Landwehr, Christoph Boeddeker, Reinhold Haeb-Umbach

We propose an approach for simultaneous diarization and separation of meeting data. It consists of a complex Angular Central Gaussian Mixture Model (cACGMM) for speech source separ…

eess.AS2024

Once more Diarization: Improving meeting transcription systems through segment-level speaker reassignment

Christoph Boeddeker, Tobias Cord-Landwehr, Reinhold Haeb-Umbach

Diarization is a crucial component in meeting transcription systems to ease the challenges of speech enhancement and attribute the transcriptions to the correct speaker. Particular…

eess.AS2024

Geodesic interpolation of frame-wise speaker embeddings for the diarization of meeting scenarios

Tobias Cord-Landwehr, Christoph Boeddeker, Cătălin Zorilă +2

We propose a modified teacher-student training for the extraction of frame-wise speaker embeddings that allows for an effective diarization of meeting scenarios containing partiall…

eess.AS2023★ 3 cited

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…

eess.AS2023★ 3 cited

A Teacher-Student approach for extracting informative speaker embeddings from speech mixtures

Tobias Cord-Landwehr, Christoph Boeddeker, Cătălin Zorilă +2

We introduce a monaural neural speaker embeddings extractor that computes an embedding for each speaker present in a speech mixture. To allow for supervised training, a teacher-stu…

eess.AS2023

Frame-wise and overlap-robust speaker embeddings for meeting diarization

Tobias Cord-Landwehr, Christoph Boeddeker, Cătălin Zorilă +2

Using a Teacher-Student training approach we developed a speaker embedding extraction system that outputs embeddings at frame rate. Given this high temporal resolution and the fact…

eess.AS2022

MMS-MSG: A Multi-purpose Multi-Speaker Mixture Signal Generator

Tobias Cord-Landwehr, Thilo von Neumann, Christoph Boeddeker +1

The scope of speech enhancement has changed from a monolithic view of single, independent tasks, to a joint processing of complex conversational speech recordings. Training and eva…

eess.AS2022★ 2 cited

A Meeting Transcription System for an Ad-Hoc Acoustic Sensor Network

Tobias Gburrek, Christoph Boeddeker, Thilo von Neumann +3

We propose a system that transcribes the conversation of a typical meeting scenario that is captured by a set of initially unsynchronized microphone arrays at unknown positions. It…

cs.SD2022★ 1 cited

An Initialization Scheme for Meeting Separation with Spatial Mixture Models

Christoph Boeddeker, Tobias Cord-Landwehr, Thilo von Neumann +1

Spatial mixture model (SMM) supported acoustic beamforming has been extensively used for the separation of simultaneously active speakers. However, it has hardly been considered fo…

eess.AS2021

Monaural source separation: From anechoic to reverberant environments

Tobias Cord-Landwehr, Christoph Boeddeker, Thilo von Neumann +3

Impressive progress in neural network-based single-channel speech source separation has been made in recent years. But those improvements have been mostly reported on anechoic data…