Cite this DOI

Latha, J., & Rani, G. (2021). Devanagari Script using Energy of Speech Signal. *Journal of Science & Technology*, *06*(01), 167–171. https://doi.org/10.46243/jst.2021.v6.i1.pp167-171

@article{latha2021devanagari,
  author    = {Latha, J.Sneha and Rani, G.Usha},
  title     = {{Devanagari Script using Energy of Speech Signal}},
  journal   = {Journal of Science \& Technology},
  year      = {2021},
  volume    = {06},
  number    = {01},
  pages     = {167--171},
  publisher = {Longman Publishers},
  issn      = {2456-5660},
  doi       = {10.46243/jst.2021.v6.i1.pp167-171},
  url       = {https://doi.org/10.46243/jst.2021.v6.i1.pp167-171},
  language  = {en},
  abstract  = {The voiced-unvoiced decision is often used in speech analysis to extract information from speech signals. Voiced and unvoiced components of speech were separated using two approaches in this study. ZCR and energy are the terms used to describe these concepts. Using the zero crossing rate and energy estimates, we were able to differentiate the voiced and unvoiced sections of the speech in this study. As a consequence of these findings, it seems that zero crossing rates for voiced and unvoiced parts are different, with the former having a higher energy level and the latter having a lower one. Because of this, they have been shown to be more adept in separating spoken and unspoken language. Devnagari script, zero crossing rate, and voice signal energy are among the key terms}
}

TY  - JOUR
TI  - Devanagari Script using Energy of Speech Signal
AU  - Latha, J.Sneha
AU  - Rani, G.Usha
JO  - Journal of Science & Technology
PY  - 2021
DA  - 2021///
VL  - 06
IS  - 01
SP  - 167
EP  - 171
PB  - Longman Publishers
SN  - 2456-5660
LA  - en
AB  - The voiced-unvoiced decision is often used in speech analysis to extract information from speech signals. Voiced and unvoiced components of speech were separated using two approaches in this study. ZCR and energy are the terms used to describe these concepts. Using the zero crossing rate and energy estimates, we were able to differentiate the voiced and unvoiced sections of the speech in this study. As a consequence of these findings, it seems that zero crossing rates for voiced and unvoiced parts are different, with the former having a higher energy level and the latter having a lower one. Because of this, they have been shown to be more adept in separating spoken and unspoken language. Devnagari script, zero crossing rate, and voice signal energy are among the key terms
DO  - 10.46243/jst.2021.v6.i1.pp167-171
UR  - https://doi.org/10.46243/jst.2021.v6.i1.pp167-171
ER  -

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    "DOI": "10.46243/jst.2021.v6.i1.pp167-171",
    "URL": "https://doi.org/10.46243/jst.2021.v6.i1.pp167-171",
    "title": "Devanagari Script using Energy of Speech Signal",
    "source": "Smart Scholars DOI Registry",
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    "author": [
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            "family": "Latha",
            "given": "J.Sneha"
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    "volume": "06",
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    "page": "167-171",
    "publisher": "Longman Publishers",
    "language": "en",
    "abstract": "The voiced-unvoiced decision is often used in speech analysis to extract information from speech signals. Voiced and unvoiced components of speech were separated using two approaches in this study. ZCR and energy are the terms used to describe these concepts. Using the zero crossing rate and energy estimates, we were able to differentiate the voiced and unvoiced sections of the speech in this study. As a consequence of these findings, it seems that zero crossing rates for voiced and unvoiced parts are different, with the former having a higher energy level and the latter having a lower one. Because of this, they have been shown to be more adept in separating spoken and unspoken language. Devnagari script, zero crossing rate, and voice signal energy are among the key terms",
    "ISSN": "2456-5660"
}

From the record as registered (version 2) — the record and its history. Programs: https://registry.smartscholars.in/api.php?action=cite&doi=10.46243%2Fjst.2021.v6.i1.pp167-171 gives all four in one JSON answer.