Signal segmentation and its application in the feature extraction of speech
Speech is considered as a time-varying signal since the parameters of the signal such as the amplitude, frequency and phase varies in time. Segmenting a duration of captured speech into analysis frames of 20 msecs ensures the assumption of stationarity. If a captured speech segment representing a wo...
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| Format: | Article |
| Language: | en |
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2000
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| Online Access: | http://eprints.utm.my/2300/1/Rahman2000__SignalSegmentationandItsApplication.pdf http://eprints.utm.my/2300/ |
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| author | Abdul Rahman, Ahmad Idil Shaikh Salleh, Sheikh Hussain Sha’ameri, Ahmad Zuri AI-Attas, Syed Abdul Rahman |
| author_facet | Abdul Rahman, Ahmad Idil Shaikh Salleh, Sheikh Hussain Sha’ameri, Ahmad Zuri AI-Attas, Syed Abdul Rahman |
| author_sort | Abdul Rahman, Ahmad Idil |
| building | UTM Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Malaysia |
| content_source | UTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Speech is considered as a time-varying signal since the parameters of the signal such as the amplitude, frequency and phase varies in time. Segmenting a duration of captured speech into analysis frames of 20 msecs ensures the assumption of stationarity. If a captured speech segment representing a word that may last for 600 msec, then a total of 30 analysis frames are required to the word. Due to the possibility that adjacent frames are identical, then it would be of interest to combine these frames into a single long frame. The interval where adjacent frames have identical parameters is referred as the time-invariant interval (TII). It is of interest to determine these intervals and two methods presented are the instantaneous energy and frequency estimation (IEFE) and localized time correlation (LTC) function. A comparison is made in the accuracy in the TII estimate for a set of speech samples |
| format | Article |
| id | my.utm.eprints-2300 |
| institution | Universiti Teknologi Malaysia |
| language | en |
| publishDate | 2000 |
| record_format | eprints |
| spelling | my.utm.eprints-23002010-06-01T03:02:23Z http://eprints.utm.my/2300/ Signal segmentation and its application in the feature extraction of speech Abdul Rahman, Ahmad Idil Shaikh Salleh, Sheikh Hussain Sha’ameri, Ahmad Zuri AI-Attas, Syed Abdul Rahman TK Electrical engineering. Electronics Nuclear engineering Speech is considered as a time-varying signal since the parameters of the signal such as the amplitude, frequency and phase varies in time. Segmenting a duration of captured speech into analysis frames of 20 msecs ensures the assumption of stationarity. If a captured speech segment representing a word that may last for 600 msec, then a total of 30 analysis frames are required to the word. Due to the possibility that adjacent frames are identical, then it would be of interest to combine these frames into a single long frame. The interval where adjacent frames have identical parameters is referred as the time-invariant interval (TII). It is of interest to determine these intervals and two methods presented are the instantaneous energy and frequency estimation (IEFE) and localized time correlation (LTC) function. A comparison is made in the accuracy in the TII estimate for a set of speech samples 2000-09-25 Article PeerReviewed application/pdf en http://eprints.utm.my/2300/1/Rahman2000__SignalSegmentationandItsApplication.pdf Abdul Rahman, Ahmad Idil and Shaikh Salleh, Sheikh Hussain and Sha’ameri, Ahmad Zuri and AI-Attas, Syed Abdul Rahman (2000) Signal segmentation and its application in the feature extraction of speech. TENCON 2000. Proceedings , 1 . pp. 265-270. |
| spellingShingle | TK Electrical engineering. Electronics Nuclear engineering Abdul Rahman, Ahmad Idil Shaikh Salleh, Sheikh Hussain Sha’ameri, Ahmad Zuri AI-Attas, Syed Abdul Rahman Signal segmentation and its application in the feature extraction of speech |
| title | Signal segmentation and its application in the feature extraction of speech |
| title_full | Signal segmentation and its application in the feature extraction of speech |
| title_fullStr | Signal segmentation and its application in the feature extraction of speech |
| title_full_unstemmed | Signal segmentation and its application in the feature extraction of speech |
| title_short | Signal segmentation and its application in the feature extraction of speech |
| title_sort | signal segmentation and its application in the feature extraction of speech |
| topic | TK Electrical engineering. Electronics Nuclear engineering |
| url | http://eprints.utm.my/2300/1/Rahman2000__SignalSegmentationandItsApplication.pdf http://eprints.utm.my/2300/ |
| url_provider | http://eprints.utm.my/ |