Audiovisual speech recognition in acoustic noisy environments using statistical techniques
| dc.contributor.guide | M Siddappa and V Udayashankara | |
| dc.coverage.spatial | ||
| dc.creator.researcher | Amaresh P Kandagal | |
| dc.date.accessioned | 2022-02-25T06:55:14Z | |
| dc.date.available | 2022-02-25T06:55:14Z | |
| dc.date.awarded | 2018 | |
| dc.date.completed | 2018 | |
| dc.date.registered | 2013 | |
| dc.description.abstract | Speech is the primary mode to exchange information between entities. Speech newlinerecognition system provides ease and natural interface for man-machine interaction (Human- newlineComputer Interaction) in our day-to-day activity to reap maximum benefit from them. newlineInteracting with smart devices in native languages has a great advantage to the society. The newlineinteraction between humans and technology is changing and automatic speech recognition is a newlinedriving force in this process. The growth of speech recognition applications over the past years newlinehas been remarkable. An important factor in this growth is the mobile telecommunications newlineindustry, which provides demand for speech recognition systems and also drives the newlinedevelopment of signal processing technology, essential to speech recognition.Speech Recognition (is also known as Automatic Speech Recognition (ASR), or newlinecomputer speech recognition) is the process by which a machine maps an acoustic signal to newlinesome form of abstract meaning of the spoken information and translates it in the form of text newlineor command by means of an algorithm implemented as a computer program. newline newline | |
| dc.description.note | ||
| dc.format.accompanyingmaterial | DVD | |
| dc.format.dimensions | 35 | |
| dc.format.extent | 15003 | |
| dc.identifier.uri | http://hdl.handle.net/10603/365124 | |
| dc.language | English | |
| dc.publisher.institution | Electronics and Communication Engineering | |
| dc.publisher.place | Tumkur | |
| dc.publisher.university | Sri Siddhartha Academy of Higher Education | |
| dc.relation | ||
| dc.rights | university | |
| dc.source.university | University | |
| dc.subject.keyword | Engineering | |
| dc.subject.keyword | Engineering and Technology | |
| dc.subject.keyword | Engineering Electrical and Electronic | |
| dc.title | Audiovisual speech recognition in acoustic noisy environments using statistical techniques | |
| dc.title.alternative | ||
| dc.type.degree | Ph.D. |
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