5 citations · 9 across the 6 of their papers we have counts for
8 papers
Selective Augmentation: Improving Universal Automatic Phonetic Transcription via G2P Bootstrapping
Tobias Bystrich, Julia M. Pritzen, Christoph A. Schmidt +1
In the field of universal automatic phonetic transcription (APT), clean and diverse training transcriptions are required. However, such high-quality data is limited. We propose the…
NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translation
Quchen Fu, Zhongwei Teng, Marco Georgaklis +2
Translating natural language into Bash Commands is an emerging research field that has gained attention in recent years. Most efforts have focused on producing more accurate transl…
Human and Automatic Speech Recognition Performance on German Oral History Interviews
Michael Gref, Nike Matthiesen, Christoph Schmidt +2
Automatic speech recognition systems have accomplished remarkable improvements in transcription accuracy in recent years. On some domains, models now achieve near-human performance…
Multitask Learning for Grapheme-to-Phoneme Conversion of Anglicisms in German Speech Recognition
Julia Pritzen, Michael Gref, Dietlind Zühlke +1
Anglicisms are a challenge in German speech recognition. Due to their irregular pronunciation compared to native German words, automatically generated pronunciation dictionaries of…
Multi-Staged Cross-Lingual Acoustic Model Adaption for Robust Speech Recognition in Real-World Applications -- A Case Study on German Oral History Interviews
Michael Gref, Oliver Walter, Christoph Schmidt +2
While recent automatic speech recognition systems achieve remarkable performance when large amounts of adequate, high quality annotated speech data is used for training, the same s…
Two-Staged Acoustic Modeling Adaption for Robust Speech Recognition by the Example of German Oral History Interviews
Michael Gref, Christoph Schmidt, Sven Behnke +1
In automatic speech recognition, often little training data is available for specific challenging tasks, but training of state-of-the-art automatic speech recognition systems requi…