Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Most current attempts at automatic speech recognition are formulated in an artificial intelligence framework.   approach the problem from an information-theoretic point of view.  describe the overall structure of a linguistic statistical decoder (LSD) for the recognition of continuous speech. The input to the decoder is a string of phonetic symbols estimated by an acoustic processor (AP). For each phonetic string, the decoder finds the most likely input sentence. The decoder consists of four major subparts: 1) a statistical model of the language being recognized; 2) a phonemic dictionary and statistical phonological rules characterizing the speaker; 3) a phonetic matching algorithm that computes the similarity beten phonetic strings, using the performance characteristics of the AP; 4) a word level search control. The details of each of the subparts and their interaction during the decoding process are discussed.
['Frederick Jelinek', 'Lalit R. Bahl', 'Robert L. Mercer']
I am writing a research paper on a idea Design of a linguistic statistical decoder for the recognition of continuous speech
[{"from": "human", "value": "I am writing a research paper on a idea Design of a linguistic statistical decoder for the recognition of continuous speech"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Most current attempts at automatic speech recognition are formulated in an artificial intelligence framework.   approach the problem from an information-theoretic point of view.  describe the overall structure of a linguistic statistical decoder (LSD) for the recognition of continuous speech. The input to the decoder is a string of phonetic symbols estimated by an acoustic processor (AP). For each phonetic string, the decoder finds the most likely input sentence. The decoder consists of four major subparts: 1) a statistical model of the language being recognized; 2) a phonemic dictionary and statistical phonological rules characterizing the speaker; 3) a phonetic matching algorithm that computes the similarity beten phonetic strings, using the performance characteristics of the AP; 4) a word level search control. The details of each of the subparts and their interaction during the decoding process are discussed."}]