Automatic speech

Automatic Speech Recognition (ASR) is a technology that converts spoken language into written text. This technology has a wide range of applications, from transcription services to voice-controlled assistants and more.

Overview

Automatic Speech Recognition is a technology that uses algorithms to convert speech into text. It is a subfield of computational linguistics that develops methodologies and technologies that enable the recognition and translation of spoken language into text by computers. It is also known as speech to text (STT).

History

The history of automatic speech recognition can be traced back to the 1950s with the Audrey system, developed by Bell Labs. This early system could recognize digits spoken by a single voice. Over the decades, the technology has evolved significantly, with modern systems capable of recognizing continuous, natural speech.

Technology

Automatic speech recognition technology involves several key components, including acoustic modeling, language modeling, and decoder.

Acoustic Modeling

Acoustic modeling involves the actual recognition of speech. It is the process of establishing statistical representations for each distinct sound made in a language.

Language Modeling

Language modeling is the process of developing a statistical model that can predict the probability of a given sequence of words occurring in a sentence.

Decoder

The decoder takes the acoustic and language models and uses them to determine the most likely word or sequence of words that produces the given input speech.

Applications

Automatic speech recognition has a wide range of applications, including transcription services, voice-controlled assistants, and more. It is used in Google Assistant, Siri, Amazon Alexa, and other similar technologies.

Challenges

Despite its advancements, automatic speech recognition technology still faces several challenges, such as handling accents, dealing with background noise, and understanding context.

See Also

• Speech synthesis
• Natural language processing
• Voice recognition
• Artificial intelligence

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