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Found 4 papers, 2 papers with code
Netmarble AI Center’s WMT21 Automatic Post-Editing Shared Task Submission
As experimental results show, our APE system significantly improves the translations of provided MT results by -2. 848 and +3. 74 on the development dataset in terms of TER and BLEU, respectively.
RWEN-TTS: Relation-aware Word Encoding Network for Natural Text-to-Speech Synthesis
With the advent of deep learning, a huge number of text-to-speech (TTS) models which produce human-like speech have emerged.
Netmarble AI Center's WMT21 Automatic Post-Editing Shared Task Submission
As experimental results show, our APE system significantly improves the translations of provided MT results by -2. 848 and +3. 74 on the development dataset in terms of TER and BLEU, respectively.
Mel-spectrogram augmentation for sequence to sequence voice conversion
In addition, we proposed new policies (i. e., frequency warping, loudness and time length control) for more data variations.
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