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Found 6 papers, 0 papers with code
Multi-paraphrase Augmentation to Leverage Neural Caption Translation
In this paper, we investigate and utilize neural paraphrasing to improve translation quality in neural MT (NMT), which has not yet been much explored.
Benefiting from Language Similarity in the Multilingual MT Training: Case Study of Indonesian and Malaysian
The development of machine translation (MT) has been successful in breaking the language barrier of the world’s top 10-20 languages.
Rakuten’s Participation in WAT 2022: Parallel Dataset Filtering by Leveraging Vocabulary Heterogeneity
This paper introduces our neural machine translation system’s participation in the WAT 2022 shared translation task (team ID: sakura).
RakutenAI-7B: Extending Large Language Models for Japanese
We introduce RakutenAI-7B, a suite of Japanese-oriented large language models that achieve the best performance on the Japanese LM Harness benchmarks among the open 7B models.
Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework
Previous research has proposed a machine speech chain to enable automatic speech recognition (ASR) and text-to-speech synthesis (TTS) to assist each other in semi-supervised learning and to avoid the need for a large amount of paired speech and text data.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+7
Listening while Speaking and Visualizing: Improving ASR through Multimodal Chain
Previously, a machine speech chain, which is based on sequence-to-sequence deep learning, was proposed to mimic speech perception and production behavior.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+7
