4 accepted papers
For several decades, chemical knowledge has been published in written text, and there have been many attempts to make it accessible, for example, by transforming such natural language text to a structured format. Although the discovered chemical itself commonly represented in an image is the most im…
While the end-to-end speech recognition models show impressive performance on many domains, they have difficulties in decoding long-form utterances. The overlapped inference algorithm with tie-breaking between two parallel hypotheses has been proposed for long-form speech recognition and shows drama…
Knowledge distillation (KD) approach is widely used in the deep learning field mainly for model size reduction. KD utilizes soft labels of teacher model, which contain the dark- knowledge that one-hot ground-truth does not have. This knowledge can improve the performance of already saturated student…
Most automatic speech recognition (ASR) neural network models are not suitable for mobile devices due to their large model sizes. Therefore, it is required to reduce the model size to meet the limited hardware resources. In this study, we investigate sequence-level knowledge distillation techniques…