Speech recognition using Artificial Intelligence (AI) is a software technology powered by advanced solutions such as Natural Language Processing (NLP) and Machine Learning (ML). NLP could be called human language processing because it is an AI technology that processes natural human speaking. The recorded voice data is first converted to a digital form that computer software can process. The digitized data is further processed by the NLP, ML, and deep learning technologies. This digitized speech can then be used for consumer solutions like smart phones, smart homes, and other voice-activated solutions.
What Is Speech Recognition?
Speech recognition is an AI-enhanced technology converting human speech from an analog form to digital form. Advanced computer programs then use the digital speech for further processing. Speech recognition is a computer receiving dictation and is different from NLP. NLP technology helps to understand the digitized dictated speech captured by speech recognition. One technology simply learns speech data. The other attempts to comprehend and respond to the speech data.
How Speech Recognition Uses AI
Speech recognition uses the AI technologies of NLP, ML, and deep learning to process voice data input. It is a data analysis technology that is not pre-programmed explicitly. ML is fed large volumes of data, and using algorithms, recognizes patterns. ML learns data from data. Then a text result or other form of output is provided. Some of the tasks that NLP uses to break down the digitized language are:
· Part of speech tagging, such as discerning between a noun or verb regarding the same word.
· Word sense disambiguation, distinguishes a word meaning from multiple possibilities.
· Named entity recognition, determines if a word is a location or a name, for example.
· Co-reference resolution, attempts to discern nuances of meaning regarding the same word.
· Sentiment analysis, attempts to detect subjective feelings or moods.
· Natural language generation, changes structured information into human language.
Speech Recognition Examples
Voice Activated Digital Assistants
These are smart phone and computer features such as Siri, Alexa, Cortana. These are voice activated and draw information from a vast number of available databases and other digitized sources to respond to commands or answer questions. These digital assistants transform the way people interact with their devices.
Speech Recognition Solutions In Banking
Voice recognition helps banking customers with their personalized queries and responds to such requests as account balances, transactions, and payments. It can improve customer care satisfaction and loyalty.
Voice Recognition In Healthcare
Healthcare often demands quick decision-making and responses. Being able to direct patient care with the voice, freeing the hands of medical professionals, improves both the speed and quality of healthcare. Less paperwork is needed. Health records can be easily accessed. Nursing staff can be reminded of appointments. It can improve hospital bedding administration. It can improve patient data inputting and change service delivery in healthcare.
Speech recognition software solutions powered by AI technologies of NLP and ML bring invaluable conveniences in accomplishing basic queries and simple tasks. These advantages can improve time use and eliminate many mundane tasks. Voice activated technologies enhance the customer experience, providing satisfying advantages both at home and work