In this task, you will be presented with a context from an academic paper and a question separated with a 
. You have to answer the question based on the context.

We collect utterances from the $\mathbf {C}$hinese $\mathbf {A}$rtificial $\mathbf {I}$ntelligence $\mathbf {S}$peakers (CAIS), and annotate them with slot tags and intent labels. The training, validation and test sets are split by the distribution of intents, where detailed statistics are provided in the supplementary material. Since the utterances are collected from speaker systems in the real world, intent labels are partial to the PlayMusic option. We adopt the BIOES tagging scheme for slots instead of the BIO2 used in the ATIS, since previous studies have highlighted meaningful improvements with this scheme BIBREF30 in the sequence labeling field. 
 Question: What is the domain of their collected corpus?
speaker systems in the real world

These workers completed 1001 tasks: 496 tasks in the control and 505 in the AUI.  
 Question: How many responses did they obtain?
1001

The 10-fold cross validation with this setting gave a token-level accuracy of roughly 71%.  
 Question: Does the paper report translation accuracy for an automatic translation model for Tunisian to Arabish words?

Yes