NeurIPS 2021poster12 citations
Timers and Such: A Practical Benchmark for Spoken Language Understanding with Numbers
Loren Lugosch, Piyush Papreja, Mirco Ravanelli, Abdelwahab HEBA, Titouan Parcollet
Abstract
This paper introduces Timers and Such, a new open source dataset of spoken English commands for common voice control use cases involving numbers. We describe the gap in existing spoken language understanding datasets that Timers and Such fills, the design and creation of the dataset, and experiments with a number of ASR-based and end-to-end baseline models, the code for which has been made available as part of the SpeechBrain toolkit.
spoken language understandingspeech recognitionopen source data
BibTeX
@inproceedings{
lugosch2021timers,
title={Timers and Such: A Practical Benchmark for Spoken Language Understanding with Numbers},
author={Loren Lugosch and Piyush Papreja and Mirco Ravanelli and Abdelwahab HEBA and Titouan Parcollet},
booktitle={Thirty-fifth Conference on Neural Information Processing Systems Datasets and Benchmarks Track (Round 1)},
year={2021},
url={https://openreview.net/forum?id=HrhaC-bLC5U}
}