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http://hdl.handle.net/10603/25496
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DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Computer Science | en_US |
dc.date.accessioned | 2014-09-23T09:57:15Z | - |
dc.date.available | 2014-09-23T09:57:15Z | - |
dc.date.issued | 2014-09-23 | - |
dc.identifier.uri | http://hdl.handle.net/10603/25496 | - |
dc.description.abstract | newline Speech is the primary most prominent and convenient means of communication in newlineaudible language Through speech people can express their thoughts feelings or perceptions by the articulation of words Human speech is a complex signal which is non stationary in nature It consists of immensely rich information about the words spoken accent attitude of the speaker expression intention sex emotion as well as style The main objective of Automatic Speech Recognition is to identify whatever people speak by means of newlinecomputer algorithms This enables people to communicate with a computer in a natural spoken language Automatic recognition of speech by machines has been one of the most exciting significant and challenging areas of research in the field of signal processing over the past five to six decades Despite the developments and intensive research done in this area the performance of ASR is still lower than that of speech recognition by humans and is yet to achieve a completely reliable performance level The main objective of this thesis is to develop an efficient speech recognition system for recognising speaker independent isolated words in Malayalam newline | en_US |
dc.format.extent | - | en_US |
dc.language | English | en_US |
dc.relation | - | en_US |
dc.rights | university | en_US |
dc.title | A hybrid architecture for recognising speech signals in Malayalam | en_US |
dc.title.alternative | - | en_US |
dc.creator.researcher | Sonia Sunny | en_US |
dc.subject.keyword | Automatic Speech Recognition | en_US |
dc.subject.keyword | Spectral Feature Extraction | en_US |
dc.subject.keyword | Speech Recognition Systems | en_US |
dc.subject.keyword | Speech Recognition System using LPC | en_US |
dc.subject.keyword | Speech Recognition System using MFCC | en_US |
dc.description.note | - | en_US |
dc.contributor.guide | David Peter S and Poulose, Jacob K | en_US |
dc.publisher.place | Cochin | en_US |
dc.publisher.university | Cochin University of Science and Technology | en_US |
dc.publisher.institution | Department of Computer Science | en_US |
dc.date.registered | 14/6/2008 | en_US |
dc.date.completed | 05/09/2013 | en_US |
dc.date.awarded | 14/03/2014 | en_US |
dc.format.dimensions | - | en_US |
dc.format.accompanyingmaterial | None | en_US |
dc.source.university | University | en_US |
dc.type.degree | Ph.D. | en_US |
Appears in Departments: | Department of Computer Science |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 67.44 kB | Adobe PDF | View/Open |
02_certificate.pdf | 58.18 kB | Adobe PDF | View/Open | |
03_declaration.pdf | 53.81 kB | Adobe PDF | View/Open | |
04_acknowledgement.pdf | 62.27 kB | Adobe PDF | View/Open | |
05_abstract.pdf | 64.38 kB | Adobe PDF | View/Open | |
06_contents.pdf | 79.03 kB | Adobe PDF | View/Open | |
07_list of tables.pdf | 50.57 kB | Adobe PDF | View/Open | |
08_list of figures.pdf | 76.08 kB | Adobe PDF | View/Open | |
09_abbreviations.pdf | 45.27 kB | Adobe PDF | View/Open | |
10_chapter 1.pdf | 729.2 kB | Adobe PDF | View/Open | |
11_chapter 2.pdf | 829.27 kB | Adobe PDF | View/Open | |
12_chapter 3.pdf | 5.59 MB | Adobe PDF | View/Open | |
13_chapter 4.pdf | 1.57 MB | Adobe PDF | View/Open | |
14_chapter 5.pdf | 1.05 MB | Adobe PDF | View/Open | |
15_chapter 6.pdf | 1.21 MB | Adobe PDF | View/Open | |
16_chapter 7.pdf | 1.48 MB | Adobe PDF | View/Open | |
17_chapter 8.pdf | 1.34 MB | Adobe PDF | View/Open | |
18_chapter 9.pdf | 419.44 kB | Adobe PDF | View/Open | |
19_references.pdf | 380.56 kB | Adobe PDF | View/Open | |
20_appendix.pdf | 2.33 MB | Adobe PDF | View/Open | |
20_publications.pdf | 243 kB | Adobe PDF | View/Open |
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