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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]
Shrutlekhan-Rajbhasha is a Hindi language speech recognition software application developed by C-DAC in collaboration with IBM [1] [clarification needed].It takes Hindi sound as input and converts to Devanagari text as output.
A text-to-speech system (or "engine") is composed of two parts: [3] a front-end and a back-end. The front-end has two major tasks. First, it converts raw text containing symbols like numbers and abbreviations into the equivalent of written-out words. This process is often called text normalization, pre-processing, or tokenization.
Hindustani does not distinguish between [v] and [w], specifically Hindi. These are distinct phonemes in English, but conditional allophones of the phoneme /ʋ/ in Hindustani (written व in Hindi or و in Urdu), meaning that contextual rules determine when it is pronounced as [v] and when it is pronounced as [w].
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Indic OCR refers to the process of converting text images written in Indic scripts into e-text using Optical character recognition (OCR) techniques. Broadly, it can also refer to the OCR systems of Brahmic scripts for languages of South Asia and Southeast Asia, not just the scripts of the Indian subcontinent, which are all written in an abugida-based writing system.
It provides a set of symbols to represent the pronunciation of Hindi and Urdu in Wikipedia articles, and example words that illustrate the sounds that correspond to them. Integrity must be maintained between the key and the transcriptions that link here; do not change any symbol or value without establishing consensus on the talk page first.
Schwa deletion is computationally important because it is essential to building text-to-speech software for Hindi. [6] [7] As a result of schwa syncope, the Hindi pronunciation of many words differs from that expected from a literal Sanskrit-style reading of Devanagari.
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