Welcome to the SLUE Benchmark¶
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We introduce the Spoken Language Understanding Evaluation (SLUE) benchmark. The goals of our work are to
Track research progress on multiple SLU tasks
Facilitate the development of pre-trained representations by providing fine-tuning and eval sets for a variety of SLU tasks
Foster the open exchange of research by focusing on freely available datasets that all academic and industrial groups can easily use.
For this benchmark, we provide new annotation of publicly available, natural speech data for training and evaluation. We also provide a benchmark suite including code to download and pre-process the SLUE datasets, train the baseline models, and evaluate performance on SLUE tasks. Refer to Toolkit and Paper for more details.
Suwon Shon - ASAPP
Felix Wu - ASAPP
Pablo Brusco - ASAPP
Kyu J. Han - ASAPP
Karen Livescu - TTI at Chicago
Ankita Pasad - TTI at Chicago
Yoav Artzi - Cornell University
Questions and issues¶
For open discussion, we will use GitHub issue page as our official Q&A boards.
For other general questions, please email us slue-committee “AT” googlegroups.com
Logo of the SLUE¶
Note that the logo of SLUE is not a snake, but a audio waveform in time-domain drawn with ascii character. We believe this text-drawn waveform represent the SLUE project properly. We use this generator to generate the waveform and sligltly modified.