SLURP: A Spoken Language Understanding Resource Package

• URL: http://arxiv.org/abs/2011.13205v1
• Date: Thu, 26 Nov 2020 09:58:20 GMT
• Title: SLURP: A Spoken Language Understanding Resource Package
• Authors: Emanuele Bastianelli, Andrea Vanzo, Pawel Swietojanski, Verena Rieser
• Abstract summary: Spoken Language Understanding infers semantic meaning directly from audio data, and thus promises to reduce error propagation and misunderstandings in end-user applications. In this paper, we release SLURP, a new SLU package containing the following:. A new dataset in English spanning 18 domains, which is substantially bigger and linguistically more diverse than existing datasets;. Competitive baselines based on state-of-the-art NLU and ASR systems;. A new transparent metric for entity labelling which enables a detailed error analysis for identifying potential areas of improvement.
• Score: 14.152975136933753
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Spoken Language Understanding infers semantic meaning directly from audio data, and thus promises to reduce error propagation and misunderstandings in end-user applications. However, publicly available SLU resources are limited. In this paper, we release SLURP, a new SLU package containing the following: (1) A new challenging dataset in English spanning 18 domains, which is substantially bigger and linguistically more diverse than existing datasets; (2) Competitive baselines based on state-of-the-art NLU and ASR systems; (3) A new transparent metric for entity labelling which enables a detailed error analysis for identifying potential areas of improvement. SLURP is available at https: //github.com/pswietojanski/slurp.

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