Application of Fuzzy Mathematics to Speech-to-Text Conversion by Elimination of Paralinguistic Content
This work addresses the problem of improving speech-to-text conversion for users in AI and human-computer interaction, but appears incremental as it builds on existing techniques with a new mathematical approach.
The paper tackles the challenge of developing automatic speech recognition systems that can mimic human-like communication by applying fuzzy mathematics to address core problems, particularly in eliminating paralinguistic content, but does not provide concrete numerical results.
For the past few decades, man has been trying to create an intelligent computer which can talk and respond like he can. The task of creating a system that can talk like a human being is the primary objective of Automatic Speech Recognition. Various Speech Recognition techniques have been developed in theory and have been applied in practice. This paper discusses the problems that have been encountered in developing Speech Recognition, the techniques that have been applied to automate the task, and a representation of the core problems of present day Speech Recognition by using Fuzzy Mathematics.