Название: Speech Recognition and UnderstandingАвтор: Zoran Gacovski
Издательство: Arcler Press
Год: 2022
Страниц: 428
Язык: английский
Формат: pdf (true)
Размер: 13.7 MB
This book entitled, "Introduction to Speech and Language Therapy", has been designed to add to the knowledge of researchers, scholars and the students of second language learners to enlighten them with various aspects of the speech, the language and the methods and techniques of its acquisition. It takes the readers through an overview of speech and language therapy and how these concepts assist the children and the adults in gaining the intricate nuances of the language. It also talks about the role and technique of speech and language proper and its assessment in the teaching of second language. Additionally, the book sheds light on the linguistic theories of speech, the teaching of language for children and the techniques of vocabulary development.
Automatic Speech Recognition (ASR) is one of the greatest technical challenges of modern times and has been attracting the attention of researchers around the world for more than half a century. As with all speech technologies, this is a multidisciplinary problem that requires knowledge in many areas, from acoustics, phonetics and linguistics, to mathematics, telecommunications, signal processing and programming. A special problem is the fact that it is a problem that is extremely language-dependent.
Speech recognition or speech to text includes capturing and digitizing the sound waves, transformation of basic linguistic units or phonemes, constructing words from phonemes and contextually analyzing the words to ensure the correct spelling of words that sounds the same. Approach: Studying the possibility of designing a software system using one of the techniques of Artificial Intelligence (AI) applications neuron networks where this system is able to distinguish the sound signals and neural networks of irregular users. Fixed weights are trained on those forms first and then the system gives the output match for each of these formats and high speed. The proposed neural network study is based on solutions of speech recognition tasks, detecting signals using angular modulation and detection of modulated techniques.
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