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Difference Between Voice Recognition And Natural Language Processing
Speech recognition is a technology that enables a computer to identify and interpret words and phrases in spoken language and convert them into texts by computers. Speech recognition tools are used in different types of dictation tasks, such as composing a text message, playing music through a home-connected device, or text-to-speech applications with virtual assistants.
Natural Language Processing
Natural Language Processing (NLP) is a branch of artificial intelligence that investigates the use of computers to process or to understand human languages for the purpose of performing useful tasks. It combines computational linguistics, computing science, cognitive science and artificial intelligence to perform tasks such as translation, automatic summarization, topic segmentation, relationship extraction, information retrieval, machine translation, and speech recognition.
Difference between Speech Recognition and Natural Language Processing
Voice recognition, also referred to as speech recognition, is a technology that offers great advantages for many types of human-machine communication. With speech recognition, computers can understand and interpret spoken words of phrases and convert them into text.
Speech recognition means talking to a computer and getting it to understand and interpret your spoken words. Speech recognition software use different algorithms to identify spoken languages and convert it into text. NLP is used to perform tasks such as automatic summarization, topic segmentation, relationship extraction, information retrieval, and speech recognition.
SR is a subfield of computational linguistics that deals with technologies to allow spoken input into systems. NLP is a technology that develops methodologies and algorithms that take as input or produce as output unstructured, natural language data.
SR is a popular speech recognition software include windows speech recognition, google assistant and dragon. In NLP, Alexa, Siri and Cortana are some of the best examples of natural language processing.
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