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| Content Provider | Springer Nature Link |
|---|---|
| Author | Kotnik, Bojan Vlaj, Damjan Horvat, Bogomir |
| Copyright Year | 2003 |
| Abstract | The evolution of robust speech recognition systems that maintain a high level of recognition accuracy in difficult and dynamically-varying acoustical environments is becoming increasingly important as speech recognition technology becomes a more integral part of mobile applications. In distributed speech recognition (DSR) architecture the recogniser's front-end is located in the terminal and is connected over a data network to a remote back-end recognition server. The terminal performs the feature parameter extraction, or the front-end of the speech recognition system. These features are transmitted over a data channel to the remote back-end recogniser. DSR provides particular benefits for the applications of mobile devices such as improved recognition performance compared to using the voice channel and ubiquitous access from different networks with a guaranteed level of recognition performance. A feature extraction algorithm integrated into the DSR system is required to operate in real-time as well as with the lowest possible computational costs.In this paper, two innovative front-end processing techniques for noise robust speech recognition are presented and compared, time-domain based frame-attenuation (TD-FrAtt) and frequency-domain based frame-attenuation (FD-FrAtt). These techniques include different forms of frame-attenuation, improvement of spectral subtraction based on minimum statistics, as well as a mel-cepstrum feature extraction procedure. Tests are performed using the Slovenian SpeechDat II fixed telephone database and the Aurora 2 database together with the HTK speech recognition toolkit. The results obtained are especially encouraging for mobile DSR systems with limited sizes of available memory and processing power. |
| Starting Page | 205 |
| Ending Page | 219 |
| Page Count | 15 |
| File Format | |
| ISSN | 13812416 |
| Journal | International Journal of Speech Technology |
| Volume Number | 6 |
| Issue Number | 3 |
| e-ISSN | 15728110 |
| Language | English |
| Publisher | Kluwer Academic Publishers |
| Publisher Date | 2003-01-01 |
| Publisher Place | Boston |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Artificial Intelligence (incl. Robotics) Signal, Image and Speech Processing Communication |
| Content Type | Text |
| Resource Type | Article |
| Subject | Human-Computer Interaction Computer Vision and Pattern Recognition Software Linguistics and Language |
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