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Subject = Signal processing ;
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Displaying Results 1 - 13 of 13 on page 1 of 1
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A code excited linear predictive coder: using a moments algorithm
(1993)
Meehan, David
A code excited linear predictive coder: using a moments algorithm
(1993)
Meehan, David
Abstract:
A speech coding algorithm was developed which was based on a new method of selecting the excitation signal from a codebook of residual error sequences. The residual error sequences in the codebook were generated from 512 frames of real speech signals. L.P.C. inverse filtering was used to obtain the residual signal. Each residual error signal was assigned an index. The index was generated using a moments algorithm. These indices were stored on a Graded Binary Tree. A Binary Search was then used to select the correct index. The use of a Graded Binary Tree in the coding algorithm reduced the search time. The algorithm faithfully reproduced the original speech when the test residual error signal was chosen from the training data. When the test residual error signal was outside the training data, synthetic speech of a recognisable quality was produced. Finally, the fundamentals of speech coders are discussed in detail and various developments are suggested.
http://doras.dcu.ie/19070/
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A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video
(2004)
Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
A framework for event detection in field-sports video broadcasts based on SVM generated audio-visual feature model. Case-study: soccer video
(2004)
Sadlier, David A.; O'Connor, Noel E.; Murphy, Noel; Marlow, Seán
Abstract:
In this paper we propose a novel audio-visual feature-based framework, for event detection in field sports broadcast video. The system is evaluated via a case-study involving MPEG encoded soccer video. Specifically, the evidence gathered by various feature detectors is combined by means of a learning algorithm (a support vector machine), which infers the occurrence of an event, based on a model generated during a training phase, utilizing a corpus of 25 hours of content. The system is evaluated using 25 hours of separate test content. Following an evaluation of results obtained, it is shown for this case, that both high precision and recall statistics are achievable.
http://doras.dcu.ie/399/
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Mark
An EEG Image-search dataset: a first-of-its-kind in IR/IIR. NAILS: neurally augmented image labelling strategies
(2017)
Healy, Graham; Wang, Zhengwei; Gurrin, Cathal; Ward, Tomás E.; Smeaton, Alan F.
An EEG Image-search dataset: a first-of-its-kind in IR/IIR. NAILS: neurally augmented image labelling strategies
(2017)
Healy, Graham; Wang, Zhengwei; Gurrin, Cathal; Ward, Tomás E.; Smeaton, Alan F.
Abstract:
In this work we emphasize the need for and we describe a first- of-its-kind RSVP (Rapid Serial Visual Presentation) - EEG (Elec- troencephalography) dataset to be released as part of the NTCIR-13 NAILS (Neurally Augmented Image Labelling Strategies) task at the NTCIR-13 participation conference. The dataset is used to support a collaborative evaluation task in which participating researchers benchmark machine-learning strategies against each other. The experimental protocol used to capture the dataset is designed to encompass a broad range of image search activities and coincident neural signals. Here, we outline the experimental protocol used to capture the dataset alongside discussing the motivation behind its construction.
http://doras.dcu.ie/21757/
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Convolutive non-negative matrix factorisation with a sparseness constraint
(2006)
Pearlmutter, Barak A.; O'Grady, Paul D.
Convolutive non-negative matrix factorisation with a sparseness constraint
(2006)
Pearlmutter, Barak A.; O'Grady, Paul D.
Abstract:
Discovering a representation which allows auditory data to be parsimoniously represented is useful for many machine learning and signal processing tasks. Such a representation can be constructed by non-negative matrix factorisation (NMF), a method for finding parts-based representations of non-negative data. We present an extension to NMF that is convolutive and includes a sparseness constraint. In combination with a spectral magnitude transform, this method discovers auditory objects and their associated sparse activation patterns.
http://mural.maynoothuniversity.ie/1375/
Marked
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Drum Source Separation using Percussive Feature Detection and Spectral Modulation
(2005)
Barry, Dan; Fitzgerald, Derry; Coyle, Eugene; Lawlor, Bob
Drum Source Separation using Percussive Feature Detection and Spectral Modulation
(2005)
Barry, Dan; Fitzgerald, Derry; Coyle, Eugene; Lawlor, Bob
Abstract:
We present a method for the separation and resynthesis of drum sources from single channel polyphonic mixtures. The frequency domain technique involves identifying the presence of a drum using a novel percussive feature detection function, after which the short-time magnitude spectrum is estimated and scaled according to an estimated time-amplitude function derived from the percussive measure. In addition to producing high quality separation results, the method we describe is also a useful pre-process for drum transcription techniques such as Prior Subspace Analysis in the presence of pitched instruments.
http://mural.maynoothuniversity.ie/699/
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Evaluating a dancer's performance using Kinect-based skeleton tracking
(2011)
O'Connor, Noel E.; Kelly, Philip
Evaluating a dancer's performance using Kinect-based skeleton tracking
(2011)
O'Connor, Noel E.; Kelly, Philip
Abstract:
In this work, we describe a novel system that automatically evaluates dance performances against a gold-standard performance and provides visual feedback to the performer in a 3D virtual environment. The system acquires the motion of a performer via Kinect-based human skeleton tracking, making the approach viable for a large range of users, including home enthusiasts. Unlike traditional gaming scenarios, when the motion of a user must by kept in synch with a pre-recorded avatar that is displayed on screen, the technique described in this paper targets online interactive scenarios where dance choreographies can be set, altered, practiced and refined by users. In this work, we have addressed some areas of this application scenario. In particular, a set of appropriate signal processing and soft computing methodologies is proposed for temporally aligning dance movements from two different users and quantitatively evaluating one performance against another.
http://doras.dcu.ie/16574/
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Input Disturbance Rejection in Channel Signal-to-Noise Ratio Constrained Feedback Control
(2008)
Rojas, A.J.; Middleton, R.H.; Freudenberg, J.S.; Braslavsky, J.H.
Input Disturbance Rejection in Channel Signal-to-Noise Ratio Constrained Feedback Control
(2008)
Rojas, A.J.; Middleton, R.H.; Freudenberg, J.S.; Braslavsky, J.H.
Abstract:
Communication channels impose a number of obstacles to feedback control. One recent line of work considers the problem of feedback stabilisation subject to a constraint on the channel signal-to-noise ratio (SNR). It has been shown for continuous-time systems that the optimal control problem of achieving the infimal SNR can be formulated as a linear quadratic Gaussian (LQG) control problem with weights chosen as in the loop transfer recovery (LTR) technique. The present paper extends this formulation to: discretetime systems; communications over channels with memory; and input disturbance rejection. By using this formulation, we derive exact expressions for the linear time invariant (LTI) controller that achieves the infimal SNR under the effect of time-delay and additive coloured noise. We then quantify the infimal SNR required for both stabilisation and input disturbance rejection for a relative degree one, minimum phase plant and a memoryless Gaussian channel.
http://mural.maynoothuniversity.ie/2245/
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Linear program differentiation for single-channel speech separation
(2006)
Pearlmutter, Barak A.; Olsson, Rasmus K.
Linear program differentiation for single-channel speech separation
(2006)
Pearlmutter, Barak A.; Olsson, Rasmus K.
Abstract:
Many apparently difficult problems can be solved by reduction to linear programming. Such problems are often subproblems within larger systems. When gradient optimisation of the entire larger system is desired, it is necessary to propagate gradients through the internally-invoked LP solver. For instance, when an intermediate quantity z is the solution to a linear program involving constraint matrix A, a vector of sensitivities dE/dz will induce sensitivities dE/dA. Here we show how these can be efficiently calculated, when they exist. This allows algorithmic differentiation to be applied to algorithms that invoke linear programming solvers as subroutines, as is common when using sparse representations in signal processing. Here we apply it to gradient optimisation of over complete dictionaries for maximally sparse representations of a speech corpus. The dictionaries are employed in a single-channel speech separation task, leading to 5 dB and 8 dB target-to-interference ratio improve...
http://mural.maynoothuniversity.ie/1376/
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Overview of NTCIR-13 NAILS task
(2017)
Healy, Graham; Ward, Tomás E.; Gurrin, Cathal; Smeaton, Alan F.
Overview of NTCIR-13 NAILS task
(2017)
Healy, Graham; Ward, Tomás E.; Gurrin, Cathal; Smeaton, Alan F.
Abstract:
In this paper we review the NTCIR-13 NAILS (Neurally Augmented Image Labelling Strategies) pilot task at NTCIR-13. We describe a first-of-its-kind RSVP (Rapid Serial Visual Presentation) - EEG (Electroencephalography) dataset released as part of the NTCIR-13 participation conference and the results of the participating organisations who benchmarked machine-learning strategies against each other using the provided unlabelled test data.
http://doras.dcu.ie/22150/
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Quantifying the 2.5D imaging performance of digital holographic systems
(2011)
Kelly, D.P.; Healy, J.J.; Hennelly, Bryan M.; Sheridan, J. T.
Quantifying the 2.5D imaging performance of digital holographic systems
(2011)
Kelly, D.P.; Healy, J.J.; Hennelly, Bryan M.; Sheridan, J. T.
Abstract:
Digital holographic systems are a class of two step, opto-numerical, three-dimensional imaging techniques. The role of the digital camera in limiting the resolution and field of view of the reconstructed image, and the interaction of these limits with a general optical system is poorly understood. The linear canonical transform describes any optical system consisting of lenses and/or free space in a unified manner. Expressions derived using it are parametrised in terms of the parameters of the optical system, as well as those of the digital camera: aperture size, pixel size and pixel pitch. We develop rules of thumb for selecting an optical system to minimise mean squared error for given input and digital camera parameters. In the limit, our results constitute a point spread function analysis. The results presented in this paper will allow digital holography practitioners to select an optical system to maximise the quality of their reconstructed image using a priori knowledge of the c...
http://mural.maynoothuniversity.ie/5786/
Marked
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Quick sift(QSIFT), an approach to reduce SIFT computational cost
(2018)
Fazel, Zahra; Famouri, Mahmoud; Nazemi, Azadeh; Azimifar, Zohreh
Quick sift(QSIFT), an approach to reduce SIFT computational cost
(2018)
Fazel, Zahra; Famouri, Mahmoud; Nazemi, Azadeh; Azimifar, Zohreh
Abstract:
SIFT has been proven to be the most robust local rotation and illumination invariant feature descriptor. Being fully scale invariant is the most important advantage of this descriptor. The major drawback of SIFT is time complexity which prevents utilizing SIFT in real-time applications. This paper describes a method to increase the speed of SIFT feature extraction using keypoint estimation and approximation instead of keypoint calculation in various scales. This research attempts to decrease SIFT computational cost without sacrificing performance and propose quick SIFT method (QSIFT). The recent researches in this area have approved that direct feature value computation is more expensive than the value extrapolation. Consequently, the contribution of this research is to reduces the time execution without losing accuracy.
http://doras.dcu.ie/23502/
Marked
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Speech-music discrimination from MPEG-1 bitstream
(2001)
Jarina, Roman; Murphy, Noel; O'Connor, Noel E.; Marlow, Seán
Speech-music discrimination from MPEG-1 bitstream
(2001)
Jarina, Roman; Murphy, Noel; O'Connor, Noel E.; Marlow, Seán
Abstract:
This paper describes a proposed algorithm for speech/music discrimination, which works on data directly taken from MPEG encoded bitstream thus avoiding the computationally difficult decoding-encoding process. The method is based on thresholding of features derived from the modulation envelope of the frequency-limited audio signal. The discriminator is tested on more than 2 hours of audio data, which contain clean and noisy speech from several speakers and a variety of music content. The discriminator is able to work in real time and despite its simplicity, results are very promising.
http://doras.dcu.ie/332/
Marked
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Use your powers wisely: resource allocation in parallel channels
(2006)
Pearlmutter, Barak A.; Jaramillo, Santiago
Use your powers wisely: resource allocation in parallel channels
(2006)
Pearlmutter, Barak A.; Jaramillo, Santiago
Abstract:
This study evaluates various resource allocation strategies for simultaneous estimation of two independent signals from noisy observations. We focus on strategies that make use of the underlying dynamics of each signal, exploiting the difference in estimation uncertainty between them. This evaluation is done empirically, by exploring the parameter space through computer simulations. Two cases are studied: one in which an initial allocation is maintained during estimation of the variables, and one in which allocation can be dynamically changed at each time step according to the uncertainty of the estimate from each channel. The results suggest that there are conditions in which it is advantageous to assign a high signal-to-noise ratio (SNR) to only one of the signals and guess the other one. Furthermore, comparison between the two allocation strategies shows that the dynamic strategy significantly improves estimation performance in low SNR scenarios when the signals have similar dyna...
http://mural.maynoothuniversity.ie/1361/
Displaying Results 1 - 13 of 13 on page 1 of 1
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Dublin City University (7)
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