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140203 ||| eng |
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|a 9783319031163
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| 100 |
1 |
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|a Rao, K. Sreenivasa
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| 245 |
0 |
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|a Speech Processing in Mobile Environments
|h Elektronische Ressource
|c by K. Sreenivasa Rao, Anil Kumar Vuppala
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| 250 |
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|a 1st ed. 2014
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| 260 |
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|a Cham
|b Springer International Publishing
|c 2014, 2014
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| 300 |
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|a XII, 121 p. 35 illus., 2 illus. in color
|b online resource
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| 505 |
0 |
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|a Introduction -- Background and Literature Review -- Vowel Onset Point Detection from Coded and Noisy Speech -- Consonant-Vowel Recognition in Presence of Coding and Background Noise -- Spotting and Recognition of Consonant-Vowel Units from Continuous Speech -- Speaker Identification and Time Scale Modification Using VOPs -- Summary and Conclusions -- MFCC Features -- Speech Orders -- Pattern Recognition Models
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| 653 |
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|a Computer Communication Networks
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| 653 |
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|a Computer networks
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| 653 |
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|a Signal, Speech and Image Processing
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| 653 |
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|a Telecommunication
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| 653 |
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|a Communications Engineering, Networks
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| 653 |
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|a Signal processing
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| 700 |
1 |
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|a Vuppala, Anil Kumar
|e [author]
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| 041 |
0 |
7 |
|a eng
|2 ISO 639-2
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| 989 |
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|b Springer
|a Springer eBooks 2005-
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| 490 |
0 |
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|a SpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning
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| 028 |
5 |
0 |
|a 10.1007/978-3-319-03116-3
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| 856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-03116-3?nosfx=y
|x Verlag
|3 Volltext
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| 082 |
0 |
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|a 621.382
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| 520 |
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|a This book focuses on speech processing in the presence of low-bit rate coding and varying background environments. The methods presented in the book exploit the speech events which are robust in noisy environments. Accurate estimation of these crucial events will be useful for carrying out various speech tasks such as speech recognition, speaker recognition and speech rate modification in mobile environments. The authors provide insights into designing and developing robust methods to process the speech in mobile environments. Covering temporal and spectral enhancement methods to minimize the effect of noise and examining methods and models on speech and speaker recognition applications in mobile environments
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