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Hindi Speech Recognition System with Robust Front End-Back End Features
| Content Provider | Semantic Scholar |
|---|---|
| Author | Gairola, Atul Baadkar, Swapna |
| Copyright Year | 2013 |
| Abstract | The ideal aim of a speech recognition system is efficient and accurate conversion of speech signal into text message without any dependence on device, environment, and speaker. In this paper a system for Hindi speech recognition is discussed employing robust front end- back end techniques. At front end MF-PLP is used for feature extraction while continuous density HMM is used at the back end for evaluation. A comparison of MFCC, PLP & MF-PLP is also presented to show the robust characteristics of MF-PLP. |
| Starting Page | 42 |
| Ending Page | 45 |
| Page Count | 4 |
| File Format | PDF HTM / HTML |
| DOI | 10.5120/10601-5305 |
| Volume Number | 64 |
| Alternate Webpage(s) | https://www.ijcaonline.org/archives/volume64/number1/10601-5305?format=pdf |
| Alternate Webpage(s) | http://research.ijcaonline.org/volume64/number1/pxc3885305.pdf |
| Alternate Webpage(s) | https://doi.org/10.5120/10601-5305 |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |
