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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bohac, M. |
| Copyright Year | 2012 |
| Description | Author affiliation: SpeechLab, Faculty of Mechatronics, Technical University of Liberec, Studentska 2, 46117 Liberec, Czech Republic (Bohac, M.) |
| Abstract | This paper is focused on the task of detecting words of interest in an audio scene (a room, a lab or a workshop) or in a continually recorded stream of speech, music and other sounds. The solution of this task is important in many applications, e.g. for command control in houses for handicapped persons, for automating some manufacturing and logistical operations, or for information retrieval from large audio archives. We investigate the use of three keyword spotting techniques and compare them with a classic large vocabulary sp eech reco gnit ion sy st em. To evaluat e t heir performance, we specified and studied two model applications: 1) search in large audio broadcast archive; 2) voice control of an interactive system. The investigated techniques were evaluated from several points of view, namely their speed (real-time factor), accuracy (equal error rate, figure of merit, receiver op erating characteristics), the demands for training data and the impact of different types of noise. |
| Starting Page | 215 |
| Ending Page | 218 |
| File Size | 131393 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781467312431 |
| ISSN | 13342630 |
| e-ISBN | 9789537044145 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2012-09-12 |
| Publisher Place | Croatia |
| Access Restriction | Subscribed |
| Rights Holder | ELMAR (Electronics in Marines) |
| Subject Keyword | Vocabulary Speech Recognition Keyword Spotting Comparison Hidden Markov models Speech recognition Speech System Control Filler Model Testing Signal to noise ratio Speech Processing |
| Content Type | Text |
| Resource Type | Article |
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