Survey On Speech Recognition Using Hidden MARKOV Model - Pradhan, Adarsh; Paul, Nabanita; Das, Kakali; Bordoloi, Rupam Jyoti; Baruah, Dikhya (International Journal of Computer Sciences and Engineering, 2025)
Modeling a signal model for recognizing speech is a tough job. Here we will find out how Hidden Markov Model (HMM) is used in modeling speech recognition application. The steps: Preprocessing, Feature Extraction and Recognition and Hidden Markov Model which used in recognition phase, are used to design a complete Automatic Speech Recognition System (ASR). Researchers are trying to model a perfect ASR system but computer machines are not able to match up to our expectations due to lack of accuracy of matching and inefficient speed of response. In speech recognition three different approaches which are broadly used are Acoustic phonetic approach, knowledge based approach and Pattern recognition approach. This study is based on pattern recognition approach using Hidden Markov Model which is studied in detail as HMMs are found to yield best performance among all the available techniques.