Syllabic Units Automatically Segmented Data for Continuous Speech Recognition (International Journal of Innovative Research in Computer Science & Technology, 2021)
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.
Keywords: Speech Recognition; Hidden Markov Models; Databases; Natural Languages; Delay Effects