4 papers · 1 filter
NAIST Simultaneous Speech Translation System for IWSLT 2024
Yuka Ko, Ryo Fukuda, Yuta Nishikawa +9
This paper describes NAIST's submission to the simultaneous track of the IWSLT 2024 Evaluation Campaign: English-to-{German, Japanese, Chinese} speech-to-text translation and Engli…
Keep Decoding Parallel with Effective Knowledge Distillation from Language Models to End-to-end Speech Recognisers
Michael Hentschel, Yuta Nishikawa, Tatsuya Komatsu +1
This study presents a novel approach for knowledge distillation (KD) from a BERT teacher model to an automatic speech recognition (ASR) model using intermediate layers. To distil t…
Tagged End-to-End Simultaneous Speech Translation Training using Simultaneous Interpretation Data
Yuka Ko, Ryo Fukuda, Yuta Nishikawa +3
Simultaneous speech translation (SimulST) translates partial speech inputs incrementally. Although the monotonic correspondence between input and output is preferable for smaller l…
Inter-connection: Effective Connection between Pre-trained Encoder and Decoder for Speech Translation
Yuta Nishikawa, Satoshi Nakamura
In end-to-end speech translation, speech and text pre-trained models improve translation quality. Recently proposed models simply connect the pre-trained models of speech and text…