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Found 10 papers, 0 papers with code
Human and Automatic Speech Recognition Performance on German Oral History Interviews
We investigate the influence of different adaptation data on robustness and generalization for clean and noisy oral history interviews.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Multitask Learning for Grapheme-to-Phoneme Conversion of Anglicisms in German Speech Recognition
In this work, we propose a multitask sequence-to-sequence approach for grapheme-to-phoneme conversion to improve the phonetization of Anglicisms.
Multi-Staged Cross-Lingual Acoustic Model Adaption for Robust Speech Recognition in Real-World Applications - A Case Study on German Oral History Interviews
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 systems often only achieve an unsatisfactory result for tasks in domains that greatly deviate from the conditions represented by the training data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Two-Staged Acoustic Modeling Adaption for Robust Speech Recognition by the Example of German Oral History Interviews
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 requires large amounts of annotated speech.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Towards a Knowledge Graph based Speech Interface
Applications which use human speech as an input require a speech interface with high recognition accuracy.
Use of Knowledge Graph in Rescoring the N-Best List in Automatic Speech Recognition
In this paper, we have tried to see the semantic relatedness between the words in a sentence to rescore the N-best list.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+4
Extensions of the Sign Language Recognition and Translation Corpus RWTH-PHOENIX-Weather
This paper introduces the RWTH-PHOENIX-Weather 2014, a video-based, large vocabulary, German sign language corpus which has been extended over the last two years, tripling the size of the original corpus.
RWTH-PHOENIX-Weather: A Large Vocabulary Sign Language Recognition and Translation Corpus
This paper introduces the RWTH-PHOENIX-Weather corpus, a video-based, large vocabulary corpus of German Sign Language suitable for statistical sign language recognition and translation.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+5
