PLP and RASTA (and MFCC, and inversion) in Matlab using melfcc.m and invmelfcc.m. .. Another popular speech feature representation is known as RASTA-PLP, an acronym for Relative Spectral Transform - Perceptual Linear Prediction. PLP was originally proposed by Hynek Hermansky as a way of warping spectra to minimize the differences between speakers while preserving the important speech information [Herm90]. RASTA is a separate technique that applies a band-pass filter to the energy in each frequency subband in order to smooth over short-term noise variations and to remove any constant offset resulting from static spectral coloration in the speech channel e.g. from a telephone line [HermM94]. ..

References in zbMATH (referenced in 23 articles )

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  1. Atkins, Jamin; Sharma, Davinder Pal: Visualization of babble-speech interactions using Andrews curves (2016)
  2. Gonzalez-Dominguez, Javier; Lopez-Moreno, Ignacio; Moreno, Pedro J.; Gonzalez-Rodriguez, Joaquin: Frame-by-frame language identification in short utterances using deep neural networks (2015)
  3. Pitsikalis, Vassilis; Katsamanis, Athanasios; Theodorakis, Stavros; Maragos, Petros: Multimodal gesture recognition via multiple hypotheses rescoring (2015)
  4. Krey, Sebastian; Ligges, Uwe; Leisch, Friedrich: Music and timbre segmentation by recursive constrained $K$-means clustering (2014)
  5. Lee, Jong-Seok: Visual-speech-pass filtering for robust automatic lip-Reading (2014)
  6. Choi, Yong-Sun; Lee, Soo-Young: Nonlinear spectro-temporal features based on a cochlear model for automatic speech recognition in a noisy situation (2013)
  7. Kurian, Cini; Balakrishnan, Kannan: Connected digit speech recognition system for Malayalam language (2013)
  8. Shen, Haifeng; Liu, Gang; Guo, Jun: Two-stage model-based feature compensation for robust speech recognition (2012)
  9. Ligges, Uwe; Krey, Sebastian: Feature clustering for instrument classification (2011)
  10. Vorwerk, Alexander; Zeiler, Steffen; Kolossa, Dorothea; Fernandez Astudillo, Ramón; Lerch, Dennis: Use of missing and unreliable data for audiovisual speech recognition (2011)
  11. Joshi, Neil; Guan, Ling: Feature fusion applied to missing data ASR with the combination of recognizers (2010)
  12. Lü, Yong; Wu, Haiyang; Zhou, Lin; Wu, Zhenyang: Multi-environment model adaptation based on vector Taylor series for robust speech recognition (2010)
  13. Mahdi, Abdulhussain E.; Picovici, Dorel: New single-ended objective measure for non-intrusive speech quality evaluation (2010)
  14. Minematsu, Nobuaki; Asakawa, Satoshi; Suzuki, Masayuki; Qiao, Yu: Speech structure and its application to robust speech processing (2010)
  15. Hyassat, Hussein; Abu Zitar, Raed: Arabic speech recognition using SPHINX engine (2008)
  16. O’Shaughnessy, Douglas: Invited paper: Automatic speech recognition: History, methods and challenges (2008)
  17. Pisarn, Chutima; Theeramunkong, Thanaruk: Thai spelling analysis for automatic spelling speech recognition (2008)
  18. Pisarn, C.; Theeramunkong, T.: An HMM-based method for Thai spelling speech recognition (2007)
  19. Saraswathi, S.; Geetha, T.V.: Time scale modification and vocal tract length normalization for improving the performance of tamil speech recognition system implemented using language independent segmentation algorithm (2007)
  20. Lu, Lie; Zhang, Hong-Jiang: Unsupervised speaker segmentation and tracking in real-time audio content analysis (2005)

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