4 accepted papers
The integration of language models for neural machine translation has been extensively studied in the past. It has been shown that an external language model, trained on additional target-side monolingual data, can help improve translation quality. However, there has always been the assumption that…
Currently, in speech translation, the straightforward approach - cascading a recognition system with a translation system - delivers state-of-the-art results.However, fundamental challenges such as error propagation from the automatic speech recognition system still remain.To mitigate these problems…
Soft contextualized data augmentation is a recent method that replaces one-hot representation of words with soft posterior distributions of an external language model, smoothing the input of neural machine translation systems. Label smoothing is another effective method that penalizes over-confident…
Informed source separation (ISS) uses source separation for extracting audio objects out of their downmix given some pre-computed parameters. In recent years, non-negative tensor factorization (NTF) has proven to be a good choice for compressing audio objects at an encoding stage. At the decoding st…