Artificial Intelligence Advances Through Speech Recognition

Comouter Engineering

The purpose of this research study is to provide a retrospective analysis of artificial intelligence and speech recognition systems. Since speech recognition provides a great opportunity to interact and communicate with automated machines, it has become one of the most widely used technologies. It can be stated with precision that speech recognition makes life easier for its users and enables them to carry out their regular activities in a more efficient and convenient way. The purpose of this study is to provide an example of current technological developments related to artificial intelligence. Recent studies have demonstrated that speech recognition is the most critical factor affecting speech decoding. The researchers created various statistical models in order to get around these problems. A selection of the most well-known statistical models comprise hidden Markov models (HMM), lexicon models, language models (LM), and acoustic models (AM). Understanding each of these statistical models of speech recognition will be aided by the research. Additionally, researchers have developed various decoding techniques that are applied to constrained artificial languages and realistic decoding tasks. These decoding techniques include artificial intelligence, acoustic phonetics, and pattern recognition. Artificial intelligence has been acknowledged as the most dependable and efficient technique for speech recognition.

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.