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Apps such as textPlus and WhatsApp use Text-to-Speech to read notifications aloud and provide voice-reply functionality. Google Cloud Text-to-Speech is powered by WaveNet, [5] software created by Google's UK-based AI subsidiary DeepMind, which was bought by Google in 2014. [6] It tries to distinguish from its competitors, Amazon and Microsoft. [7]
One drawback of this software is that if mixed English–Hindi dictation is given, it can recognize Hindi words but can not recognize English words. Another variant of this software is Vachantar-Rajbhasha, which takes English sound as input, converts it to English text and then translates it to Hindi using MANTRA-Rajbhasha translation engine.
Deep learning speech synthesis refers to the application of deep learning models to generate natural-sounding human speech from written text (text-to-speech) or spectrum . Deep neural networks are trained using large amounts of recorded speech and, in the case of a text-to-speech system, the associated labels and/or input text.
This is an accepted version of this page This is the latest accepted revision, reviewed on 31 January 2025. Artificial production of human speech Automatic announcement A synthetic voice announcing an arriving train in Sweden. Problems playing this file? See media help. Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech ...
Google Translate is a multilingual neural machine translation service developed by Google to translate text, documents and websites from one language into another. It offers a website interface, a mobile app for Android and iOS, as well as an API that helps developers build browser extensions and software applications. [3]
Audio deepfake technology, also referred to as voice cloning or deepfake audio, is an application of artificial intelligence designed to generate speech that convincingly mimics specific individuals, often synthesizing phrases or sentences they have never spoken.
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Artificial intelligence detection software aims to determine whether some content (text, image, video or audio) was generated using artificial intelligence (AI). However, the reliability of such software is a topic of debate, [ 1 ] and there are concerns about the potential misapplication of AI detection software by educators.
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