Artificial Intelligence and Machine Learning in Speech Recognition

Posted By :Vikas Verma |31st March 2020


AI is the study of computer skills to perform tasks, currently best performed by humans. AI has an interdisciplinary field where computer science meets Philosophy, Psychology, Engineering, and other fields. People make decisions based on experience and purpose. The root of AI in computing to simulate this learning process is known as Artificial Intelligence Integration. As more and more businesses are investing in artificial intelligence development services, generation of value and customer satisfaction are witnessing an upward trend. This article discusses the role and intricacies of artificial intelligence and machine learning in speech recognition systems integrated into our everyday life. 


When you call the main company's phone numbers, you may hear the voice of a believing lady who answers your call with great kindness saying "welcome to company X, please enter the representative number you want or the extension number of the person you want to contact. When a caller receives a call, communication is provided immediately. This is a trick that works when using an automated call management system without using anyone with a telephone.



Source: Dribbble






Artificial intelligence (AI) introduces two basic concepts. First, it involves the study of human thinking processes. Second, it is about representing those processes with machines (such as computers, robots, etc.) Machine behavior, which when man-made is called intelligence. It makes machines smarter and more efficient, and less expensive than natural intelligence. Machine learning solutions including speech, image, and object recognition are beginning to transform business intelligence with deeper analytics and insights. 



Natural Language Processing (NLP) refers to ways to demonstrate computer communication skills in natural language such as English. The main purpose of the NLP program is to understand the installation and to initiate action. Keyword identification triggers a specific action. In this way, one can communicate with the computer in its own language. No special instructions or computer language are required. There is no need to install programs in a specific software architecture language.


Voice XML continues speech recognition. Instead of talking on your computer, you actually talk to a website, and you do this by phone.OK, you say, well, what exactly is speech recognition? Simply put, the process of converting spoken input into text. Speech recognition is sometimes called speech-to-text. Speech recognition allows you to provide in-app voice input. Like clicking your mouse, typing on your keyboard, or pressing a key on the phone keypad provides input into the app; Speech recognition allows you to provide verbal input. In the digital era, we need a device to interact is a microphone and device to communicate is telephone or mobile.


The process is created by a software component known as a speech recognition engine. The primary function of the speech recognition service is to process the input in question and translate it into text that is understood by the application. An application can do one of two things: An application can interpret the effect of recognition as a command In this case, the app is a command and control utility. If an application treats a received text as mere text, then it is considered as an application.


The user communicates with the computer via the microphone, which identifies the meaning of the words and sends it to the NLP device for further processing. Once employed, words can be used in many applications such as displays, robots, instructions on computers, and pronunciation.


About Author

Vikas Verma

He is frontend developer. He is a learner by heart and has a passion and profile to adapt various technologies.

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