| 1 | Title of the Article | Syllabic Units Automatically Segmented Data for Continuous Speech Recognition |
| 2 | Author's name | Madhav Singh Solanki: SOEIT, Sanskriti University, Mathura, Uttar Pradesh, India (madhavsolanki.cse@sanskriti.edu.in) |
| 3 | Author's name | |
| 4 | Subject | Computer Science |
| 5 | Keyword(s) | Speech Recognition, Hidden Markov Models, Databases, Natural Languages, Delay Effects. |
| 6 | Abstract | 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. |
| 7 | Publisher | Innovative Research Publication |
| 8 | Journal Name; vol., no. | International Journal of Innovative Research in Computer Science & Technology (IJIRCST); Volume-9 Issue-6 |
| 9 | Publication Date | November 2021 |
| 10 | Type | Peer-reviewed Article |
| 11 | Format | |
| 12 | Uniform Resource Identifier | https://ijircst.org/view_abstract.php?title=Syllabic-Units-Automatically-Segmented-Data-for-Continuous-Speech-Recognition&year=2021&vol=9&primary=QVJULTY3Mw== |
| 13 | Digital Object Identifier(DOI) | 10.55524/ijircst.2021.9.6.53 https://doi.org/10.55524/ijircst.2021.9.6.53 |
| 14 | Language | English |
| 15 | Page No | 239-242 |