49 datasets found

Multilingual pronunciation learning for Text-to-Speech systems. Phonetic information and linguistic knowledge are an essential component of a Text-to-speech (TTS) front-end.

The datasets used in the experiments are annotated according to the Unimorph schema guidelines.

MuST-C v1.0 is a multilingual corpus for end-to-end speech translation, containing 8 language pairs.

Parameter-efficient fine-tuning (PEFT) using labeled task data can significantly improve the performance of large language models (LLMs) on the downstream task. However, there...

The dataset used in the paper is a subset of the OPUS-MT dataset, containing 1M randomly sampled examples from the OPUS-100 dataset.

Europarl-ST is a multilingual speech corpus that contains transcriptions of parliamentary debates in multiple languages.

MTG is a multilingual multiway text generation benchmark suite. It is the first-proposed multilingual multiway text generation dataset with the largest human-annotated data...

The PMIndiaSum dataset contains multilingual and cross-lingual headline summarization for languages in India.

Wikipedia as multilingual source of comparable corpora.

The M4 dataset consists of human-written texts from several data sources, including Wikipedia, Reddit, and arXiv in the English subset of the dataset. It pairs the human-written...

The CLIPfa dataset is a multilingual image-text dataset.

The SemEval-2023 Visual Word Sense Disambiguation (V-WSD) Task dataset consists of a silver dataset with 12,869 V-WSD instances. Each sample is a 4-tuple ⟨f, c, I, i∗ ∈ I⟩ where...

The PAN Profiling Fake News Spreader Task contains a dataset in English, whose samples were collected from Twitter.

The PAN Profiling Hate Speech Spreader Task contains a dataset in English and Spanish, whose samples were collected from Twitter.

The BABEL-Pashto dataset is a multilingual speech recognition dataset containing Pashto speech recordings.

A multilingual African embedding for FAQ chatbots

Multilingual Neural Machine Translation datasets

The dataset used in this study is the OSCAR corpus, which is a multilingual corpus that is obtained by filtering of the Common Crawl corpus.

A collection of semantic textual relatedness datasets for African and Asian languages.

A collection of semantic textual relatedness datasets for 14 languages.