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Speech synthesis is the task of generating speech from some other modality like text, lip movements etc.
The computer-generated simulation of human speech is known as speech synthesis. It's used to convert written data into audible data when it's more convenient, notably for mobile apps like voice-enabled e-mail and unified messaging. It's also used to help the vision-impaired, so that the contents of a display screen, for example, can be read aloud to a blind person. Speech synthesis is the counterpart of speech or voice recognition just like in popular solutions like text to speech in google.

For persons with physical limitations that make it difficult to talk clearly, speech prosthesis is computer-generated speech. Because the disorders that cause speech problems typically make text entry problematic as well, much of the research in this field combines text to speech

The challenge of speech prosthesis is to avoid these challenges given the pace and fluidity of human communication. The major goal of the study is to develop a prosthetic system that mimics normal speech as nearly as possible while requiring the least amount of user input. Visually challenged people can also utilise computers thanks to speech prosthesis technologies.

But, before we get into the meat of the paper, there are a couple of traditional speech synthesis methodologies that we should go through briefly: concatenative and parametric.
Speeches from a big database are concatenated to create fresh, audible speech in the concatenative technique. A new database of audio voices is employed when a different style of speech is required. This limits the approach's scalability. You can also get any voice from text to speech.
 

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