Omkar2118/datasets huggingface dataset:
IWSLT2015
Full name: IWSLT2015

The IWSLT 2015 Evaluation Campaign featured three tracks: automatic speech recognition (ASR), spoken language translation (SLT), and machine translation (MT). For ASR we offered two tasks, on English and German, while
for SLT and MT a number of tasks were proposed, involving English, German, French, Chinese, Czech, Thai, and Vietnamese. All tracks involved the transcription or translation of TED talks, either made available by the official TED website or by other TEDx events. A notable change with respect to previous evaluations was the use of unsegmented speech in the SLT track in order to better fit a real application scenario.
DroneCrowd

**DroneCrowd** is a benchmark for object detection, tracking and counting algorithms in drone-captured videos. It is a drone-captured large scale dataset formed by 112 video clips with 33,600 HD frames in various scenarios. Notably, it has annotations for 20,800 people trajectories with 4.8 million heads and several video-level attributes.

Introducing paper: Detection, Tracking, and Counting Meets Drones in Crowds: A Benchmark