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Speech Recognition & Synthesis. Speech Recognition & Synthesis, formerly known as Speech Services, [3] is a screen reader application developed by Google for its Android operating system. It powers applications to read aloud (speak) the text on the screen, with support for many languages. Text-to-Speech may be used by apps such as Google Play ...
v. t. e. Google Neural Machine Translation (GNMT) was a neural machine translation (NMT) system developed by Google and introduced in November 2016 that used an artificial neural network to increase fluency and accuracy in Google Translate. [1][2][3][4] The neural network consisted of two main blocks, an encoder and a decoder, both of LSTM ...
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]
Speech translation is the process by which conversational spoken phrases are instantly translated and spoken aloud in a second language. This differs from phrase translation, which is where the system only translates a fixed and finite set of phrases that have been manually entered into the system. Speech translation technology enables speakers ...
The demo showed how Google’s Translate can automatically listen to speech and translate it in real-time, displaying the translated text for the wearer to see and read with ease.
Speech synthesis is the artificial production of human speech. A computer system used for this purpose is called a speech synthesizer, and can be implemented in software or hardware products. A text-to-speech (TTS) system converts normal language text into speech; other systems render symbolic linguistic representations like phonetic ...
Kural translations by language. v. t. e. Machine translation is use of computational techniques to translate text or speech from one language to another, including the contextual, idiomatic and pragmatic nuances of both languages. Early approaches were mostly rule-based or statistical.
Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content. Artificial intelligence algorithms are commonly developed and employed to achieve this, specialized for different types of data.