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Cepstrum-based pitch detection using a new statistical V/UV classification algorithm
An improved cepstrum-based voicing detection and pitch determination algorithm is presented. Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech si...
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| Published in: | IEEE transactions on speech and audio processing 1999-05, Vol.7 (3), p.333-338 |
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| Main Authors: | , |
| Format: | Article |
| Language: | English |
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| cited_by | cdi_FETCH-LOGICAL-c405t-a57e75eaa4ebe45d3e8e7e03078f8b63af1bdb3ae34f986eafbe504073f252a43 |
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| cites | cdi_FETCH-LOGICAL-c405t-a57e75eaa4ebe45d3e8e7e03078f8b63af1bdb3ae34f986eafbe504073f252a43 |
| container_end_page | 338 |
| container_issue | 3 |
| container_start_page | 333 |
| container_title | IEEE transactions on speech and audio processing |
| container_volume | 7 |
| creator | Ahmadi, S. Spanias, A.S. |
| description | An improved cepstrum-based voicing detection and pitch determination algorithm is presented. Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech signal. Pitch frequency information is extracted by a modified cepstrum-based method and then carefully refined using pitch tracking, correction, and smoothing algorithms. Performance analysis on a large database indicates considerable improvement relative to the conventional cepstrum method. The proposed algorithm is also shown to be robust to additive noise. |
| doi_str_mv | 10.1109/89.759042 |
| format | article |
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Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech signal. Pitch frequency information is extracted by a modified cepstrum-based method and then carefully refined using pitch tracking, correction, and smoothing algorithms. Performance analysis on a large database indicates considerable improvement relative to the conventional cepstrum method. The proposed algorithm is also shown to be robust to additive noise.</description><identifier>ISSN: 1063-6676</identifier><identifier>EISSN: 1558-2353</identifier><identifier>DOI: 10.1109/89.759042</identifier><identifier>CODEN: IESPEJ</identifier><language>eng</language><publisher>New York, NY: IEEE</publisher><subject>Algorithms ; Applied sciences ; Cepstral analysis ; Cepstrum ; Classification ; Classification algorithms ; Data mining ; Energy use ; Exact sciences and technology ; Frequency ; Information, signal and communications theory ; Performance analysis ; Segments ; Signal processing ; Smoothing ; Smoothing methods ; Speech ; Speech analysis ; Speech processing ; Statistical analysis ; Telecommunications and information theory ; Tracking</subject><ispartof>IEEE transactions on speech and audio processing, 1999-05, Vol.7 (3), p.333-338</ispartof><rights>1999 INIST-CNRS</rights><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c405t-a57e75eaa4ebe45d3e8e7e03078f8b63af1bdb3ae34f986eafbe504073f252a43</citedby><cites>FETCH-LOGICAL-c405t-a57e75eaa4ebe45d3e8e7e03078f8b63af1bdb3ae34f986eafbe504073f252a43</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://ieeexplore.ieee.org/document/759042$$EHTML$$P50$$Gieee$$H</linktohtml><link.rule.ids>314,780,784,27924,27925,54796</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=1773945$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Ahmadi, S.</creatorcontrib><creatorcontrib>Spanias, A.S.</creatorcontrib><title>Cepstrum-based pitch detection using a new statistical V/UV classification algorithm</title><title>IEEE transactions on speech and audio processing</title><addtitle>T-SAP</addtitle><description>An improved cepstrum-based voicing detection and pitch determination algorithm is presented. Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech signal. Pitch frequency information is extracted by a modified cepstrum-based method and then carefully refined using pitch tracking, correction, and smoothing algorithms. Performance analysis on a large database indicates considerable improvement relative to the conventional cepstrum method. The proposed algorithm is also shown to be robust to additive noise.</description><subject>Algorithms</subject><subject>Applied sciences</subject><subject>Cepstral analysis</subject><subject>Cepstrum</subject><subject>Classification</subject><subject>Classification algorithms</subject><subject>Data mining</subject><subject>Energy use</subject><subject>Exact sciences and technology</subject><subject>Frequency</subject><subject>Information, signal and communications theory</subject><subject>Performance analysis</subject><subject>Segments</subject><subject>Signal processing</subject><subject>Smoothing</subject><subject>Smoothing methods</subject><subject>Speech</subject><subject>Speech analysis</subject><subject>Speech processing</subject><subject>Statistical analysis</subject><subject>Telecommunications and information theory</subject><subject>Tracking</subject><issn>1063-6676</issn><issn>1558-2353</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1999</creationdate><recordtype>article</recordtype><recordid>eNp9kD1PwzAQhiMEElAYWJkyIARDWju2Y2dEFV9SJZa2a3RJzq1Rvsi5Qvx7UlLBxnSnu-ce6d4guOJsyjlLZyadapUyGR8FZ1wpE8VCieOhZ4mIkkQnp8E50TtjzHAtz4LlHDvy_a6OciAsw875YhuW6LHwrm3CHblmE0LY4GdIHrwj7wqowvVstQ6LCoicHQY_LFSbtnd-W18EJxYqwstDnQSrp8fl_CVavD2_zh8WUSGZ8hEojVohgMQcpSoFGtTIBNPGmjwRYHle5gJQSJuaBMHmqJhkWthYxSDFJLgdvV3ffuyQfFY7KrCqoMF2R1lsYjG8rwfw7l-QJ5oLJTlXA3o_okXfEvVos653NfRfGWfZPuLMpNkY8cDeHLRAQyi2h6Zw9HegtUjlXnk9Yg4Rf7cHxzeEnoPH</recordid><startdate>19990501</startdate><enddate>19990501</enddate><creator>Ahmadi, S.</creator><creator>Spanias, A.S.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>RIA</scope><scope>RIE</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>8FD</scope><scope>F28</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>19990501</creationdate><title>Cepstrum-based pitch detection using a new statistical V/UV classification algorithm</title><author>Ahmadi, S. ; Spanias, A.S.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c405t-a57e75eaa4ebe45d3e8e7e03078f8b63af1bdb3ae34f986eafbe504073f252a43</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1999</creationdate><topic>Algorithms</topic><topic>Applied sciences</topic><topic>Cepstral analysis</topic><topic>Cepstrum</topic><topic>Classification</topic><topic>Classification algorithms</topic><topic>Data mining</topic><topic>Energy use</topic><topic>Exact sciences and technology</topic><topic>Frequency</topic><topic>Information, signal and communications theory</topic><topic>Performance analysis</topic><topic>Segments</topic><topic>Signal processing</topic><topic>Smoothing</topic><topic>Smoothing methods</topic><topic>Speech</topic><topic>Speech analysis</topic><topic>Speech processing</topic><topic>Statistical analysis</topic><topic>Telecommunications and information theory</topic><topic>Tracking</topic><toplevel>online_resources</toplevel><creatorcontrib>Ahmadi, S.</creatorcontrib><creatorcontrib>Spanias, A.S.</creatorcontrib><collection>IEEE All-Society Periodicals Package (ASPP) 1998-Present</collection><collection>IEEE/IET Electronic Library</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Technology Research Database</collection><collection>ANTE: Abstracts in New Technology & Engineering</collection><collection>Engineering 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>IEEE transactions on speech and audio processing</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ahmadi, S.</au><au>Spanias, A.S.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Cepstrum-based pitch detection using a new statistical V/UV classification algorithm</atitle><jtitle>IEEE transactions on speech and audio processing</jtitle><stitle>T-SAP</stitle><date>1999-05-01</date><risdate>1999</risdate><volume>7</volume><issue>3</issue><spage>333</spage><epage>338</epage><pages>333-338</pages><issn>1063-6676</issn><eissn>1558-2353</eissn><coden>IESPEJ</coden><abstract>An improved cepstrum-based voicing detection and pitch determination algorithm is presented. Voicing decisions are made using a multifeature voiced/unvoiced classification algorithm based on statistical analysis of cepstral peak, zero-crossing rate, and energy of short-time segments of the speech signal. Pitch frequency information is extracted by a modified cepstrum-based method and then carefully refined using pitch tracking, correction, and smoothing algorithms. Performance analysis on a large database indicates considerable improvement relative to the conventional cepstrum method. The proposed algorithm is also shown to be robust to additive noise.</abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/89.759042</doi><tpages>6</tpages></addata></record> |
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| identifier | ISSN: 1063-6676 |
| ispartof | IEEE transactions on speech and audio processing, 1999-05, Vol.7 (3), p.333-338 |
| issn | 1063-6676 1558-2353 |
| language | eng |
| recordid | cdi_ieee_primary_759042 |
| source | IEEE Xplore (Online service) |
| subjects | Algorithms Applied sciences Cepstral analysis Cepstrum Classification Classification algorithms Data mining Energy use Exact sciences and technology Frequency Information, signal and communications theory Performance analysis Segments Signal processing Smoothing Smoothing methods Speech Speech analysis Speech processing Statistical analysis Telecommunications and information theory Tracking |
| title | Cepstrum-based pitch detection using a new statistical V/UV classification algorithm |
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