activity
20172025
most citedSMS-WSJ: Database, performance measures, and baseline recipe for multi-channel source separation and recognition

56 citations · 344 across the 33 of their papers we have counts for

collaborators
Showing 2023Show all

7 papers · 1 filter

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★ 2 cited

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…

cs.CL2023★ 3 cited

MeetEval: A Toolkit for Computation of Word Error Rates for Meeting Transcription Systems

Thilo von Neumann, Christoph Boeddeker, Marc Delcroix +1

MeetEval is an open-source toolkit to evaluate all kinds of meeting transcription systems. It provides a unified interface for the computation of commonly used Word Error Rates (WE…

cs.CL2023

Mixture Encoder for Joint Speech Separation and Recognition

Simon Berger, Peter Vieting, Christoph Boeddeker +2

Multi-speaker automatic speech recognition (ASR) is crucial for many real-world applications, but it requires dedicated modeling techniques. Existing approaches can be divided into…

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.AS2023★ 29 cited

TS-SEP: Joint Diarization and Separation Conditioned on Estimated Speaker Embeddings

Christoph Boeddeker, Aswin Shanmugam Subramanian, Gordon Wichern +2

Since diarization and source separation of meeting data are closely related tasks, we here propose an approach to perform the two objectives jointly. It builds upon the target-spea…