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Auditory based front-ends for speech recognition have been compared before, but this paper focuses on two of the most promising algorithms for noise robustness in automatic speech recognition (ASR). The feature sets are Zero-Crossings with Peak Amplitudes (ZCPA) and the recently introduced Power-Law Nonlinearity and Power-Bias Subtraction (PNCC). Standard Mel-Frequency Cepstral Coefficients (MFCC)...
Rotational types of motion can often be seen in video sequences. However, not a lot of research has been done to investigate rotational motion models for use in video. Analysing this unique type of motion could be very useful. For example, if the the centre of rotation of a spinning object can be efficiently identified, extraction and tracking of it can be made easier by grouping points moving at...
This paper describes initial work on a framework for automatic detection of illegal dumping from CCTV footage from recycle centres. Frames are seperated into foreground and background regions using a Bayesian approach that combines global motion estimates with image based information to generate a robust segmentation. The framework hence avoids explicit modelling and tracking of objects in the scene...
This paper investigates the use of voicing information as an additional cue in contrast enhanced frequency shaping (CEFS) of speech to improve perception in the hearing impaired. The presented work builds on an existing system combining multiband compression with contrast enhanced frequency shaping (MICEFS) to restore the auditory nerve response of a hearing impaired listener. CEFS can improve the...
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