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Another translation app heavyweight, Microsoft Translator, is one of the many free translation apps capable to translate text, voice, conversation, and image translations. It can perform both online and offline translations in more than 60 languages. Just like Google Translate, though, you need to download language packs to enable offline use.

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In case you would like to sound like your favorite movie star of TV host, then Celebrity Voice Changer is one of the best choices you can make. Besides the standard set of options, the app also lets you request new voices since its machine learning technology can mimic virtually anyone's voice. However, Celebrity Voice Changer is currently only available in English and it cannot modulate speech in other languages. In addition, you must make an in-app purchase in order to gain access to all of the app's features or unlock the unlimited usage of the app.

Impersonating your favorite celebrity can be a fun way to prank your friends on social media. Voicy features a broad selection of celebrity voice impersonations you can use to make you sound like a famous actress or TV personality. The app utilizes a machine learning technology that can generate more than forty avatars and allows the users to experiment with different voice effects. The free version of the app offers only limited capabilities, so if you want to gain access to all of the Voicy's features, you must choose a weekly, monthly or an annual subscription.

NarrativeQA is a data set constructed to encourage deeper understanding of language. This dataset involves reasoning about reading whole books or movie scripts. This dataset contains approximately 45,000 pairs of free text question-and-answer pairs. There are two modes of understanding this dataset: (1) reading comprehension on summaries and (2) reading comprehension on whole books/scripts.

QuAC, a data set for answering questions in context that contains 14K information-seeking QI dialogues (100K questions in total). Question Answering in Context is a dataset for modeling, understanding, and participating in information-seeking dialogues. The data instances consist of an interactive dialogue between two crowd workers: (1) a student who asks a sequence of free questions to learn as much as possible about a hidden Wikipedia text, and (2) a teacher who answers the questions by providing short excerpts (staves) of the text. QuAC introduces challenges not found in existing machine comprehension data sets: its questions are often more open-ended, unanswered, or only meaningful in the context of dialogue.

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