2 citations · 4 across the 8 of their papers we have counts for
9 papers
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…
Unified Learnable 2D Convolutional Feature Extraction for ASR
Peter Vieting, Benedikt Hilmes, Ralf Schlüter +1
Neural front-ends represent a promising approach to feature extraction for automatic speech recognition (ASR) systems as they enable to learn specifically tailored features for dif…
Regularizing Learnable Feature Extraction for Automatic Speech Recognition
Peter Vieting, Maximilian Kannen, Benedikt Hilmes +2
Neural front-ends are an appealing alternative to traditional, fixed feature extraction pipelines for automatic speech recognition (ASR) systems since they can be directly trained…
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…
Comparative Analysis of the wav2vec 2.0 Feature Extractor
Peter Vieting, Ralf Schlüter, Hermann Ney
Automatic speech recognition (ASR) systems typically use handcrafted feature extraction pipelines. To avoid their inherent information loss and to achieve more consistent modeling…
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…
Efficient Utilization of Large Pre-Trained Models for Low Resource ASR
Peter Vieting, Christoph Lüscher, Julian Dierkes +2
Unsupervised representation learning has recently helped automatic speech recognition (ASR) to tackle tasks with limited labeled data. Following this, hardware limitations and appl…
Development of Hybrid ASR Systems for Low Resource Medical Domain Conversational Telephone Speech
Christoph Lüscher, Mohammad Zeineldeen, Zijian Yang +6
Language barriers present a great challenge in our increasingly connected and global world. Especially within the medical domain, e.g. hospital or emergency room, communication dif…
On Architectures and Training for Raw Waveform Feature Extraction in ASR
Peter Vieting, Christoph Lüscher, Wilfried Michel +2
With the success of neural network based modeling in automatic speech recognition (ASR), many studies investigated acoustic modeling and learning of feature extractors directly bas…