Omkar2118/datasets huggingface dataset:
SSD
Full name: Sub-Slot Dialogue dataset

SSD (Sub-slot Dialog) dataset: This is the dataset for the ACL 2022 paper "A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots". [arxiv](https://arxiv.org/pdf/2203.10759.pdf)

Introducing paper: A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots
Banglish

A Bilingual Dataset for Bangla and English Voice Commands

Colloquial Bangla has adopted many English words due to colonial influence. In conversational Bangla, it is quite common to speak in a mixture of English and Bangla. This phenomenon, prevalent in conversational language is known as code-switching (CS). CS is defined as the continuous alternation between two languages in a single conversation. Thus, in Bangla natural language processing, it is often necessary to map a single base command to its many different variants - spoken in multiple mixtures of English and Bangla. In order to facilitate this, we have curated a dataset centered around common browser commands.
washed_contract

Dataset contains about 48K contracts which are open source on Etherscan.

Introducing paper: Semantic Code Search for Smart Contracts
DaReCzech
Full name: Dataset for text relevance ranking in Czech

## DareCzech

DaReCzech is a dataset for text relevance ranking in Czech. The dataset consists of more than 1.6M annotated query-documents pairs, which makes it one of the largest available datasets for this task.

### Obtaining the Annotated Data
Please, first read [a disclaimer](https://github.com/seznam/DaReCzech/blob/master/disclaimer.md) that contains the terms of use. If you comply with them, send an email to [srch.vyzkum@firma.seznam.cz](mailto:srch.vyzkum@firma.seznam.cz) and the link to the dataset will be sent to you.

Introducing paper: Siamese BERT-based Model for Web Search Relevance Ranking Evaluated on a New Czech Dataset
MAD

MAD (Movie Audio Descriptions) is an automatically curated large-scale dataset for the task of natural language grounding in videos or natural language moment retrieval.
MAD exploits available audio descriptions of mainstream movies. Such audio descriptions are redacted for visually impaired audiences and are therefore highly descriptive of the visual content being displayed. 
MAD contains over 384,000 natural language sentences grounded in over 1,200 hours of video, and provides a unique setup for video grounding as the visual stream is truly untrimmed with an average video duration of 110 minutes. 2 orders of magnitude longer than legacy datasets. 

Take a look at the paper for additional information.

From the authors on availability: "Due to copyright constraints, MAD’s videos will not be publicly released. However, we will provide all necessary features for our experiments’ reproducibility and promote future research in this direction"

Introducing paper: MAD: A Scalable Dataset for Language Grounding in Videos from Movie Audio Descriptions