Browsing by Subject "Subband decomposition"

Now showing 1 - 5 of 5

Open Access
Computationally efficient voice dialing system
(1998) Solmaz, Mustafa Hakan
Subband based feature parameters are becoming widely used for speech recognition purposes. In this thesis a subband-based, small-vocabulary, speaker-dependent, isolated-word recognition system is proposed. The most distinctive property of the proposed system is its low computational cost which enables it to run at real-time on a simple microcontroller. The system is used as the core of a voice dialer which is designed to work together with Karel switchboxes. In training section first, an energy-based endpoint (startingpoint) detection method is applied for speech detection. Then feature extraction is applied on a fixed length, pcm-quantized (a-law) speech long enough to cover a single word. In recognition section template matching is used to find the most likely vocabulary element. A recognition rate of 93% is obtained in the simulations.
Open Access
Linear/nonlinear adaptive polyphase subband decomposition structures for image compression
(IEEE, 1998-05) Gerek, Ömer N.; Çetin, A. Enis
Subband decomposition techniques have been extensively used for data coding and analysis. In most filter banks, the goal is to obtain subsampled signals corresponding to different spectral bands of the original data. However, this approach leads to various artifacts in images containing text, subtitles, or sharp edges. In this paper, adaptive filter banks with perfect reconstruction property are presented for such images. The filters of the decomposition structure vary according to the nature of the signal. This leads to higher compression ratios for images containing subtitles compared to fixed filter banks. Simulation examples are presented.
Open Access
A multiresolution nonrectangular wavelet representation for two-dimensional signals
(Elsevier, 1993) Çetin, A. Enis
In this paper, a new multiresolution wavelet representation for two-dimensional signals is described. This wavelet representation is based on a nonrectangular decomposition of the frequency domain. The decomposition can be implemented by a digital filter bank. The application of the new representation to the coding of quincunx and rectangularly sampled images is considered and simulation examples are presented.
Open Access
New methods for robust speech recognition
(1995) Erzin, Engin
New methods of feature extraction, end-point detection and speech enhcincement are developed for a robust speech recognition system. The methods of feature extraction and end-point detection are based on wavelet analysis or subband analysis of the speech signal. Two new sets of speech feature parameters, SUBLSF’s and SUBCEP’s, are introduced. Both parameter sets are based on subband analysis. The SUBLSF feature parameters are obtained via linear predictive analysis on subbands. These speech feature parameters can produce better results than the full-band parameters when the noise is colored. The SUBCEP parameters are based on wavelet analysis or equivalently the multirate subband analysis of the speech signal. The SUBCEP parameters also provide robust recognition performance by appropriately deemphasizing the frequency bands corrupted by noise. It is experimentally observed that the subband analysis based feature parameters are more robust than the commonly used full-band analysis based parameters in the presence of car noise. The a-stable random processes can be used to model the impulsive nature of the public network telecommunication noise. Adaptive filtering are developed for Q-stable random processes. Adaptive noise cancelation techniques are used to reduce the mismacth between training and testing conditions of the recognition system over telephone lines. Another important problem in isolated speech recognition is to determine the boundaries of the speech utterances or words. Precise boundary detection of utterances improves the performance of speech recognition systems. A new distance measure based on the subband energy levels is introduced for endpoint detection.
Open Access
Polyphase adaptive filter banks for subband decomposition
(IEEE, 1998-05-06) Gerek, Ömer N.; Çetin, A. Enis
Subband decomposition is widely used in signal processing applications including image and speech compression. In most practical cases, the goal is to obtain subband signals that are suitable for data compression. In this paper, we present Perfect Reconstruction (PR) polyphase filter bank structures in which the filters adapt to the changing input conditions. This leads to higher compression results for images containing sharp edges, text, and subtitles.