Omkar2118/datasets huggingface dataset:
Haydn Annotation Dataset

The Haydn Annotation Dataset consists of note onset annotations from 24 experiment participants with varying musical experience. The annotation experiments use recordings from the ARME Virtuoso Strings Dataset.

Source: [Annotation of Soft Onsets in String Ensemble Recordings](https://arxiv.org/pdf/2211.08848v1.pdf)

Image Source: [https://arxiv.org/pdf/2211.08848v1.pdf](https://arxiv.org/pdf/2211.08848v1.pdf)

Introducing paper: Annotation of Soft Onsets in String Ensemble Recordings
UJ-CS/Math/Phy

Definitions of jargon/terms in computer science, mathematics, and physics

Introducing paper: Understanding Jargon: Combining Extraction and Generation for Definition Modeling
APIDIS

# Data

Approximatively 2 hours of videos were captured from 7 viewpoints during a professional basketball game.

**Raw data**

The cameras were recording at almost 22 fps in average, with a resolution of 1600x1200 pixels. The video files are available in their native format, i.e. one motion jpeg file (~300 MB) per minute per camera.

**Pseudo-synchronised video**

A pseudo synchronised dataset is provided by resampling the raw videos at 25 fps (using the closest available frame) with a resolution of 800x600 pixels. The video files are available as one MPEG-4 file (between 28 MB and 56 MB) per minute per camera. For optimal timestamps accuracy, the original dataset should be prefered.

# Annotations

**Timestamps**

All timestamps are expressed in seconds since Epoch when provided as integers. When provided in a human readable format, e.g. in filenames, they follow the <a href="http://en.wikipedia.org/wiki/ISO_8601">ISO 8601</a> date/time syntax.

**Calibration**

All cameras are <a href="http://www.arecontvision.com/">Arecont Vision</a> AV2100M IP cameras (<a href="http://www.arecontvision.com/resources.php?pid=106">datasheet</a>). The fish-eye lenses used for the top view cameras are <a href="http://www.fujinon.com">Fujinon</a> FE185C086HA-1 lenses (<a href="http://www.fujifilmusa.com/products/optical_devices/security/fish-eye/5-mp/fe185c086ha-1/">datasheet</a>). Each camera was indivually calibrated into a common world coordinate system.

**Additional annotations**

Several manually annotated objects are provided (see NEM'08 summit paper):
- Basket ball events like ball possession periods, throws, violations ; for the whole basketball game
- Ball, Players and referees position ; for one minute of the game.

Annotated events and salient-objects are recorded into two kinds of XML files whose syntax is described in the XML Schema Definition (xsd) files `apidis-annotation-ver23.xsd` and `apidis-salientobj-ver1.xsd`. A simplified structural diagram of event xml files is illustrated in `event-xml-simple.png`.
The tags for describing the detected objects and their properties are illlustrated in `salient-obj-xml.png`.

Ball was annotated in the 2D images on every camera where it was visible. An approximate 3D localization is inferred for the pseudo-synchronized dataset.



# Terms of use:
This dataset is available for non-commercial research in video signal processing only. We kindly ask you to mention the APIDIS project when using this dataset (in publications, video demonstrations...).

# Acknowledgements
We would like to thank Jean-François Prior (<a href="http://www.belfiusnamurcapitale.be/">Dexia Namur</a> basket ball team), Philippe Delmulle <a href="http://www.dbcwaregem.be/">Declercq Stortbeton Waregem</a> basket ball team) and the city of <a href="http://www.namur.be/">Namur</a> for their authorisations and technical help collecting this dataset.
modified_shemo

A modification on the ShEMO dataset with help of an Automatic Speech Recognition (ASR) system.

the ShEMO dataset contains 3000 audio files along with 3000 text files for each sentence as a ground-truth transcription. The text file of the sentence related to the corresponding audio file can be found through the names of the files. In fact, the audio and the text file of an utterance have the same name. But out of 3000 files, only 2838 have the same name. With further investigations, we found that some of these text files have the wrong names and referred to the wrong audio file. We fixed the errors and inconsistencies in ShEMO dataset by using an Automatic Speech Recognition (ASR) system.

Introducing paper: A Persian ASR-based SER: Modification of Sharif Emotional Speech Database and Investigation of Persian Text Corpora
PKG sample

A random sample from Pubmed Knowledge Graph.

Introducing paper: Novelpy: A Python package to measure novelty and disruptiveness of bibliometric and patent data