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Found 10 papers, 2 papers with code
Automatic Video Dubbing at AppTek
The revoicing usually comes with a changed script, mostly in a different language, and the revoicing should reproduce the original emotions, coherent with the body language, and lip synchronized.
The RWTH Aachen Machine Translation System for IWSLT 2016
This work describes the statistical machine translation (SMT) systems of RWTH Aachen University developed for the evaluation campaign of International Workshop on Spoken Language Translation (IWSLT) 2016.
The RWTH Aachen Machine Translation Systems for IWSLT 2017
This work describes the Neural Machine Translation (NMT) system of the RWTH Aachen University developed for the English$German tracks of the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2017.
On the Relevance of Phoneme Duration Variability of Synthesized Training Data for Automatic Speech Recognition
Synthetic data generated by text-to-speech (TTS) systems can be used to improve automatic speech recognition (ASR) systems in low-resource or domain mismatch tasks.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Take the Hint: Improving Arabic Diacritization with Partially-Diacritized Text
Automatic Arabic diacritization is useful in many applications, ranging from reading support for language learners to accurate pronunciation predictor for downstream tasks like speech synthesis.
Comparing the Benefit of Synthetic Training Data for Various Automatic Speech Recognition Architectures
We achieve a final word-error-rate of 3. 3%/10. 0% with a hybrid system on the clean/noisy test-sets, surpassing any previous state-of-the-art systems on Librispeech-100h that do not include unlabeled audio data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Generating Synthetic Audio Data for Attention-Based Speech Recognition Systems
We achieve improvements of up to 33% relative in word-error-rate (WER) over a strong baseline with data-augmentation in a low-resource environment (LibriSpeech-100h), closing the gap to a comparable oracle experiment by more than 50\%.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Learning Bilingual Sentence Embeddings via Autoencoding and Computing Similarities with a Multilayer Perceptron
We propose a novel model architecture and training algorithm to learn bilingual sentence embeddings from a combination of parallel and monolingual data.
The RWTH Aachen University Filtering System for the WMT 2018 Parallel Corpus Filtering Task
We use several rule-based, heuristic methods to preselect sentence pairs.
