Content for Deep Learning: The Lionbridge View

March 17, 2020

Here is a handy resource. Lionbridge AI shares “The Best 25 Datasets for Natural Language Processing.” The list is designed as a starting point for those just delving into NLP. Writer Meiryum Ali begins:

“Natural language processing is a massive field of research. With so many areas to explore, it can sometimes be difficult to know where to begin – let alone start searching for data. With this in mind, we’ve combed the web to create the ultimate collection of free online datasets for NLP. Although it’s impossible to cover every field of interest, we’ve done our best to compile datasets for a broad range of NLP research areas, from sentiment analysis to audio and voice recognition projects. Use it as a starting point for your experiments, or check out our specialized collections of datasets if you already have a project in mind.”

The suggestions are divided by purpose. For use in sentiment analysis, Ali notes one needs to train machine learning models on large, specialized datasets like the Multidomain Sentiment Analysis Dataset or the Stanford Sentiment Treebank. Some text datasets she suggests for natural language processing tasks like voice recognition or chatbots include 20 Newsgroups, the Reuters News Dataset, and Princeton University’s WordNet. Audio speech datasets that made the list include the audiobooks of LibriSpeech, the Spoken Wikipedia Corpora, and the Free Spoken Digit Dataset. The collection concludes with some more general-purpose datasets, like Amazon Reviews, the Blogger Corpus, the Gutenberg eBooks List, and a set of questions and answers from Jeopardy. See the write-up for more on each of these entries as well as the rest of Ali’s suggestions in each category.

This being a post from Lionbridge, an AI training data firm, it naturally concludes with an invitation to contact them when ready to move beyond these pre-made datasets to one customized for you. Based in Waltham, Massachusetts, the company was founded in 1996 and acquired by H.I.G. Capital in 2017.

Cynthia Murrell, March 17, 2020

Written by Stephen E. Arnold · Filed Under AI, Database, News, Text processing

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Stephen E. Arnold monitors search, content processing, text mining and related topics from his high-tech nerve center in rural Kentucky. He tries to winnow the goose feathers from the giblets. He works with colleagues worldwide to make this Web log useful to those who want to go "beyond search". Contact him at sa [at] arnoldit.com. His Web site with additional information about search is arnoldit.com.