A text-to-speech dataset is a collection of audio recordings and their corresponding text transcriptions, which are used to train and evaluate text-to-speech systems. These datasets typically contain a large number of spoken sentences or phrases, recorded by one or multiple speakers.

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Natural Language Processing (NLP) is a subfield of artificial intelligence (AI). It enables robots to analyze and comprehend human language, enabling them to carry out repetitive activities without human intervention. Examples include machine translation, summarization, ticket classification, and spell check.

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Why accurate speech data annotation is so essential for the application and development of voice recognition technology? Let's find out in the article below.

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