Omkar2118/datasets huggingface dataset:
BGG dataset
Full name: PUBG Gun Sound Dataset

We recorded gun sounds by changing the type and
position of guns to diversify distances and angles in the
PUBG environment. The BGG dataset
consists of 2,195 samples with 37 different types of guns
and five directions, including a silence in which there is
no gunfire, but noises exist. The distance from the firearms
ranged from 0 meters to 600 meters. The audio was recorded
in stereo (i.e., two-channel audio), and each sample contains
various environmental noises (e.g., water splashing, walking,
and bullet friction).

Introducing paper: Enemy Spotted: in-game gun sound dataset for gunshot classification and localization
MIMIC-SPARQL

Question Answering (QA) is a widely-used framework for developing and evaluating an intelligent
machine. In this light, QA on Electronic Health Records (EHR), namely EHR QA, can work as
a crucial milestone toward developing an intelligent agent in healthcare. EHR data are typically
stored in a relational database, which can also be converted to a directed acyclic graph, allowing two
approaches for EHR QA: Table-based QA and Knowledge Graph-based QA.

MIMIC-SPARQL dataset provides  graph-based EHR QA data where natural language queries are converted
to SPARQL instead of SQL

Introducing paper: Knowledge Graph-based Question Answering with Electronic Health Records
VideoAttentionTarget

A dataset with fully annotated attention targets in video for attention target estimation.

Introducing paper: Detecting Attended Visual Targets in Video