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Abstract
This paper aims to present a retrospective study about speech recognition systems and artificial intelligence. Speech recognition is one of the widely used technologies, as it offers great opportunities to interact and communicate with automated machines. Precisely, it can be affirmed that speech recognition facilitate users and also helps them to perform their daily routine tasks, in a more convenient and effective manner. This research looks to present the illustration of recent technological advancements, which are associated with artificial intelligence. Recent researches has reveals the fact that speech recognition is found to be the utmost issue, which affects the decoding of speech. In order to get over these i ssues, different statistical models were developed by the researchers. Some of the most spectacular statistical models include acoustic model (AM), language model (LM), lexicon model, and hidden Markov models (HMM). This research helps in understanding all of these statistical models of speech recognition. Researchers also formulated different decoding methods, which are being utilized for realistic decoding tasks and constrained artificial languages. These decoding methods contain pattern recognition, acoustic phonetic, and artificial intelligence. It has been recognized that artificial intelligence is the most efficient and reliable method, which is being used in speech recognition.