173 citations · 306 across the 58 of their papers we have counts for
8 papers · 1 filter
Reproducing and Dissecting Denoising Language Models for Speech Recognition
Dorian Koch, Albert Zeyer, Nick Rossenbach +2
Denoising language models (DLMs) have been proposed as a powerful alternative to traditional language models (LMs) for automatic speech recognition (ASR), motivated by their abilit…
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…
A Comparative Analysis on ASR System Combination for Attention, CTC, Factored Hybrid, and Transducer Models
Noureldin Bayoumi, Robin Schmitt, Tina Raissi +3
Combination approaches for speech recognition (ASR) systems cover structured sentence-level or word-based merging techniques as well as combination of model scores during beam sear…
Exploring Gender Bias in Large Language Models: An In-depth Dive into the German Language
Kristin Gnadt, David Thulke, Simone Kopeinik +1
In recent years, various methods have been proposed to evaluate gender bias in large language models (LLMs). A key challenge lies in the transferability of bias measurement methods…
Label-Context-Dependent Internal Language Model Estimation for CTC
Zijian Yang, Minh-Nghia Phan, Ralf Schlüter +1
Although connectionist temporal classification (CTC) has the label context independence assumption, it can still implicitly learn a context-dependent internal language model (ILM)…
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…
Analyzing the Importance of Blank for CTC-Based Knowledge Distillation
Benedikt Hilmes, Nick Rossenbach, Ralf Schlüter
With the rise of large pre-trained foundation models for automatic speech recognition new challenges appear. While the performance of these models is good, runtime and cost of infe…
Classification Error Bound for Low Bayes Error Conditions in Machine Learning
Zijian Yang, Vahe Eminyan, Ralf Schlüter +1
In statistical classification and machine learning, classification error is an important performance measure, which is minimized by the Bayes decision rule. In practice, the unknow…