Open Access"Syllabic Units Automatically Segmented Data for Continuous Speech Recognition"
Author(s) -
Madhav Singh Solanki
Publication year - 2021
Publication title -
international journal of innovative research in computer science and technology
Language(s) - English
Resource type - Journals
ISSN - 2347-5552
DOI - 10.55524/ijircst.2021.9.6.53
Subject(s) - syllabic verse , speech recognition , syllable , computer science , viterbi algorithm , hidden markov model , utterance , speech processing , artificial intelligence , signal (programming language) , natural language processing , measure (data warehouse) , pattern recognition (psychology) , database , programming language
We present novel approach for constant speech processing in which the detection and recognition tasks are separated A syllable is utilized as a measure both to detection and localization. A minimal phase’s group delay characteristic approach and an utterance isolated style are used to segment the speech signal at the boundaries of syllabic units. For two Indigenous languages, an HMM recognizing system has been created. Viterbi algorithm-based methods are suggested to solve recognition problems caused by shifts in segment borders and syllabic unit merging.