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.

[Q]: We use UltraSuite: a repository of ultrasound and acoustic data gathered from child speech therapy sessions BIBREF15 . We used all three datasets from the repository: UXTD (recorded with typically developing children), and UXSSD and UPX (recorded with children with speech sound disorders). In total, the dataset contains 13,815 spoken utterances from 86 speakers, corresponding to 35.9 hours of recordings. The utterances have been categorised by the type of task the child was given, and are labelled as: Words (A), Non-words (B), Sentence (C), Articulatory (D), Non-speech (E), or Conversations (F).
Question: Do they annotate their own dataset or use an existing one?
[A]: Use an existing one

[Q]: Each passage was labelled by 3 unique annotators.
Question: How many annotators were there?
[A]: 3

[Q]: Dialogue Collection: before the formal data collection starts, we required the workers to make a small number of dialogues and gave them feedback about the dialogue quality. Then, well-trained workers were paired to converse according to the given goals. The workers were also asked to annotate both user states and system states.

Dialogue Annotation: we used some rules to automatically annotate dialogue acts according to user states, system states, and dialogue histories. To evaluate the quality of the annotation of dialogue acts and states, three experts were employed to manually annotate dialogue acts and states for 50 dialogues. The results show that our annotations are of high quality. Finally, each dialogue contains a structured goal, a task description, user states, system states, dialogue acts, and utterances.
Question: How was the corpus annotated?
[A]:
The workers were also asked to annotate both user states and system states we used some rules to automatically annotate dialogue acts according to user states, system states, and dialogue histories