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Wasserstein Selective Transfer Learning for Cross-domain Text Mining
However, the source and target domains usually have different data distributions, which may lead to negative transfer.
ASR-GLUE: A New Multi-task Benchmark for ASR-Robust Natural Language Understanding
%To facilitate the research on ASR-robust general language understanding, In this paper, we propose ASR-GLUE benchmark, a new collection of 6 different NLU tasks for evaluating the performance of models under ASR error across 3 different levels of background noise and 6 speakers with various voice characteristics.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Learning to Augment for Data-Scarce Domain BERT Knowledge Distillation
Despite pre-trained language models such as BERT have achieved appealing performance in a wide range of natural language processing tasks, they are computationally expensive to be deployed in real-time applications.
