Speaker Identification Using Discrete Wavelet Transform
This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracte...
Gespeichert in:
| Veröffentlicht in: | Journal of computer science 2015-01, Vol.11 (1), p.53-56 |
|---|---|
| Hauptverfasser: | , |
| Format: | Artikel |
| Sprache: | eng |
| Schlagworte: | |
| Online-Zugang: | Volltext |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| container_end_page | 56 |
|---|---|
| container_issue | 1 |
| container_start_page | 53 |
| container_title | Journal of computer science |
| container_volume | 11 |
| creator | Pandiaraj, Shanthini Kumar, K. R. Shankar |
| description | This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracted and used in a closed-set text-independent speaker identification task. In this study, the signals are pre-processed and features are extracted using discrete wavelet transforms. The energy of the wavelet coefficients are used for training the Gaussian Mixture Model. Daubechies wavelets are used and the speech samples are analyzed using 8 levels of decomposition. |
| doi_str_mv | 10.3844/jcssp.2015.53.56 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_cross</sourceid><recordid>TN_cdi_proquest_miscellaneous_1677956454</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><sourcerecordid>1677956454</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2336-b407ada2414bc32f1864111352b817145d3ea4f6ff7566b094008707cb4f63b33</originalsourceid><addsrcrecordid>eNotkM1LAzEUxIMoWKt3j3v0smuSl7xsj1K1FgoebPEYsumLbN0vk63gf29rPc0wDMPwY-xW8AJKpe53PqWhkFzoQkOh8YxNhNYyR-Tm_OjVLAcEvGRXKe04B5RGTph5G8h9UsyWW-rGOtTejXXfZZtUdx_ZY518pJGyd_dNDY3ZOrouhT621-wiuCbRzb9O2eb5aT1_yVevi-X8YZV7CYB5pbhxWyeVUJUHGUSJSggBWlalMELpLZBTAUMwGrHiM8V5abjx1SGECmDK7k67Q-y_9pRG2x4-UdO4jvp9sgKNmWlUWh2q_FT1sU8pUrBDrFsXf6zg9sjI_jGyR0ZWg9UIv1hgWbo</addsrcrecordid><sourcetype>Aggregation Database</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1677956454</pqid></control><display><type>article</type><title>Speaker Identification Using Discrete Wavelet Transform</title><source>Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals</source><creator>Pandiaraj, Shanthini ; Kumar, K. R. Shankar</creator><creatorcontrib>Pandiaraj, Shanthini ; Kumar, K. R. Shankar</creatorcontrib><description>This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracted and used in a closed-set text-independent speaker identification task. In this study, the signals are pre-processed and features are extracted using discrete wavelet transforms. The energy of the wavelet coefficients are used for training the Gaussian Mixture Model. Daubechies wavelets are used and the speech samples are analyzed using 8 levels of decomposition.</description><identifier>ISSN: 1549-3636</identifier><identifier>EISSN: 1552-6607</identifier><identifier>DOI: 10.3844/jcssp.2015.53.56</identifier><language>eng</language><subject>Computer simulation ; Discrete Wavelet Transform ; Energy use ; Feature extraction ; Gaussian ; Mathematical models ; Speech recognition ; Tasks ; Wavelet</subject><ispartof>Journal of computer science, 2015-01, Vol.11 (1), p.53-56</ispartof><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c2336-b407ada2414bc32f1864111352b817145d3ea4f6ff7566b094008707cb4f63b33</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,776,780,27901,27902</link.rule.ids></links><search><creatorcontrib>Pandiaraj, Shanthini</creatorcontrib><creatorcontrib>Kumar, K. R. Shankar</creatorcontrib><title>Speaker Identification Using Discrete Wavelet Transform</title><title>Journal of computer science</title><description>This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracted and used in a closed-set text-independent speaker identification task. In this study, the signals are pre-processed and features are extracted using discrete wavelet transforms. The energy of the wavelet coefficients are used for training the Gaussian Mixture Model. Daubechies wavelets are used and the speech samples are analyzed using 8 levels of decomposition.</description><subject>Computer simulation</subject><subject>Discrete Wavelet Transform</subject><subject>Energy use</subject><subject>Feature extraction</subject><subject>Gaussian</subject><subject>Mathematical models</subject><subject>Speech recognition</subject><subject>Tasks</subject><subject>Wavelet</subject><issn>1549-3636</issn><issn>1552-6607</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2015</creationdate><recordtype>article</recordtype><recordid>eNotkM1LAzEUxIMoWKt3j3v0smuSl7xsj1K1FgoebPEYsumLbN0vk63gf29rPc0wDMPwY-xW8AJKpe53PqWhkFzoQkOh8YxNhNYyR-Tm_OjVLAcEvGRXKe04B5RGTph5G8h9UsyWW-rGOtTejXXfZZtUdx_ZY518pJGyd_dNDY3ZOrouhT621-wiuCbRzb9O2eb5aT1_yVevi-X8YZV7CYB5pbhxWyeVUJUHGUSJSggBWlalMELpLZBTAUMwGrHiM8V5abjx1SGECmDK7k67Q-y_9pRG2x4-UdO4jvp9sgKNmWlUWh2q_FT1sU8pUrBDrFsXf6zg9sjI_jGyR0ZWg9UIv1hgWbo</recordid><startdate>20150101</startdate><enddate>20150101</enddate><creator>Pandiaraj, Shanthini</creator><creator>Kumar, K. R. Shankar</creator><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20150101</creationdate><title>Speaker Identification Using Discrete Wavelet Transform</title><author>Pandiaraj, Shanthini ; Kumar, K. R. Shankar</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2336-b407ada2414bc32f1864111352b817145d3ea4f6ff7566b094008707cb4f63b33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2015</creationdate><topic>Computer simulation</topic><topic>Discrete Wavelet Transform</topic><topic>Energy use</topic><topic>Feature extraction</topic><topic>Gaussian</topic><topic>Mathematical models</topic><topic>Speech recognition</topic><topic>Tasks</topic><topic>Wavelet</topic><toplevel>online_resources</toplevel><creatorcontrib>Pandiaraj, Shanthini</creatorcontrib><creatorcontrib>Kumar, K. R. Shankar</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Journal of computer science</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pandiaraj, Shanthini</au><au>Kumar, K. R. Shankar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Speaker Identification Using Discrete Wavelet Transform</atitle><jtitle>Journal of computer science</jtitle><date>2015-01-01</date><risdate>2015</risdate><volume>11</volume><issue>1</issue><spage>53</spage><epage>56</epage><pages>53-56</pages><issn>1549-3636</issn><eissn>1552-6607</eissn><abstract>This study presents an experimental evaluation of Discrete Wavelet Transforms for use in speaker identification. The features are tested using speech data provided by the CHAINS corpus. This system consists of two stages: Feature extraction stage and the identification stage. Parameters are extracted and used in a closed-set text-independent speaker identification task. In this study, the signals are pre-processed and features are extracted using discrete wavelet transforms. The energy of the wavelet coefficients are used for training the Gaussian Mixture Model. Daubechies wavelets are used and the speech samples are analyzed using 8 levels of decomposition.</abstract><doi>10.3844/jcssp.2015.53.56</doi><tpages>4</tpages><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1549-3636 |
| ispartof | Journal of computer science, 2015-01, Vol.11 (1), p.53-56 |
| issn | 1549-3636 1552-6607 |
| language | eng |
| recordid | cdi_proquest_miscellaneous_1677956454 |
| source | Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
| subjects | Computer simulation Discrete Wavelet Transform Energy use Feature extraction Gaussian Mathematical models Speech recognition Tasks Wavelet |
| title | Speaker Identification Using Discrete Wavelet Transform |
| url | https://sfx.bib-bvb.de/sfx_tum?ctx_ver=Z39.88-2004&ctx_enc=info:ofi/enc:UTF-8&ctx_tim=2025-02-03T00%3A33%3A00IST&url_ver=Z39.88-2004&url_ctx_fmt=infofi/fmt:kev:mtx:ctx&rfr_id=info:sid/primo.exlibrisgroup.com:primo3-Article-proquest_cross&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.genre=article&rft.atitle=Speaker%20Identification%20Using%20Discrete%20Wavelet%20Transform&rft.jtitle=Journal%20of%20computer%20science&rft.au=Pandiaraj,%20Shanthini&rft.date=2015-01-01&rft.volume=11&rft.issue=1&rft.spage=53&rft.epage=56&rft.pages=53-56&rft.issn=1549-3636&rft.eissn=1552-6607&rft_id=info:doi/10.3844/jcssp.2015.53.56&rft_dat=%3Cproquest_cross%3E1677956454%3C/proquest_cross%3E%3Curl%3E%3C/url%3E&disable_directlink=true&sfx.directlink=off&sfx.report_link=0&rft_id=info:oai/&rft_pqid=1677956454&rft_id=info:pmid/&rfr_iscdi=true |