parts of visual form computational aspects underlying recognition is an organization of objects and their parts into classes and hierarchies a representation of parts for recognition requires that they be invariant to rigid transformations robust in the presence of occlusions stable with changes in viewing geometry and be arranged in a hierarchy these constraints are captured in a general framework using notions of a part line and a partitioning scheme a proposed general principle of form from function motivates a particular partitioning scheme involving two types of parts neck based and limb based neck based parts arise from narrowings in shape or the local minima in distance between two points on the boundary while limb based parts arise from a pair of negative curvature minima which have co circular tangents in this paper we present computational support for the limb based and neck based parts by showing that they are invariant robust stable and yield a hierarchy of parts examples illustrate that the resulting decompositions are robust in the presence of occlusion and clutter for a range of man made and natural objects and lead to natural and intuitive parts which can be used for recognition

factors affecting the use of noise band vocoders as acoustic models for pitch perception in cochlear implants although in a number of experiments noise band vocoders have been shown to provide acoustic models for speech perception in cochlear implants ci the present study assesses in four experiments whether and under what limitations noise band vocoders can be used as an acoustic model for pitch perception in ci the first two experiments examine the effect of spectral smearing on simulated electrode discrimination and fundamental frequency f0 discrimination the third experiment assesses the effect of spectral mismatch in an f0 discrimination task with two different vocoders the fourth experiment investigates the effect of amplitude compression on modulation rate discrimination for each experiment the results obtained from normal hearing subjects presented with vocoded stimuli are compared to results obtained directly from ci recipients the results show that place pitch sensitivity drops with increased spectral smearing and that place pitch cues for multi channel stimuli can adequately be mimicked when

a penalized likelihood approach to image warping discussion a warping is a function that deforms images by mapping between image domains the choice of function is formulated statistically as maximum penalized likelihood where the likelihood measures the similarity between images after warping and the penalty is a measure of distortion of a warping the paper addresses two issues simultaneously of how to choose the warping function and how to assess the alignment a new fourier von mises image model is identified with phase differences between fourier transformed images having von mises distributions also new null set distortion criteria are proposed with each criterion uniquely minimized by a particular set of polynomial functions a conjugate gradient algorithm is used to estimate the warping function which is numerically approximated by a piecewise bilinear function the method is motivated by and used to solve three applied problems to register a remotely sensed image with a map to align microscope images obtained by using different optics and to discriminate between species of fish from photographic images

scale based description and recognition of planar curves and two dimensional shapes the problem of finding a description at varying levels of detail for planar curves and matching two such descriptions is posed and solved in this paper a number of necessary criteria are imposed on any candidate solution method path based gaussian smoothing techniques are applied to the curve to find zeros of curvature at varying levels of detail the result is the generalized scale space image of a planar curve which is invariant under rotation uniform scaling and translation of the curve these properties make the scale space image suitable for matching the matching algorithm is a modification of the uniform cost algorithm and finds the lowest cost match of contours in the scale space images it is argued that this is preferable to matching in a so called stable scale of the curve because no such scale may exist for a given curve this technique is applied to register a landsat satellite image of the strait of georgia b c manually corrected for skew to a map containing the shorelines of an overlapping area

invariant image recognition by zernike moments the problem of rotation scale and translation invariant recognition of images is discussed a set of rotation invariant features are introduced they are the magnitudes of a set of orthogonal complex moments of the image known as zernike moments scale and translation invariance are obtained by first normalizing the image with respect to these parameters using its regular geometrical moments a systematic reconstruction based method for deciding the highest order zernike moments required in a classification problem is developed the quality of the reconstructed image is examined through its comparison to the original one the orthogonality property of the zernike moments which simplifies the process of image reconstruction make the suggest feature selection approach practical features of each order can also be weighted according to their contribution to the reconstruction process the superiority of zernike moment features over regular moments and moment invariants was experimentally verified

effects of spectral smearing and temporal fine structure distortion on the fluctuating masker benefit for speech at a fixed signal to noise ratio normal hearing listeners receive less benefit from momentary dips in the level of a fluctuating masker for speech processed to degrade spectral detail or temporal fine structure tfs than for unprocessed speech this has been interpreted as evidence that the magnitude of the fluctuating masker benefit fmb reflects the ability to resolve spectral detail and tfs however the fmb for degraded speech is typically measured at a higher signal to noise ratio snr to yield performance similar to normal speech for the baseline stationary noise condition because the fmb decreases with increasing snr this snr difference might account for the reduction in fmb for degraded speech in this study the fmb for unprocessed and processed tfs removed or spectrally smeared speech was measured in a paradigm that adjusts word set size rather than snr to equate stationary noise performance across processing conditions compared at the same snr and percent correct level but with different set sizes processed and unprocessed stimuli yielded a similar fmb for four different fluctuating maskers speech modulated noise one opposite gender interfering talker two same gender interfering talkers and 16 hz interrupted noise these results suggest that for these maskers spectral or tfs distortions do not directly impair the ability to benefit from momentary dips in masker level

shape retrieval based on dynamic programming we propose a shape matching algorithm for deformed shapes based on dynamic programming our algorithm is capable of grouping together segments at finer scales in order to come up with appropriate correspondences with segments at coarser scales we illustrate the effectiveness of our algorithm in retrieval of shapes by content on two different two dimensional 2 d datasets one of static hand gesture shapes and another of marine life shapes we also demonstrate the superiority of our approach over traditional approaches to shape matching and retrieval such as fourier descriptors and geometric and sequential moments our evaluation is based on human relevance judgments following a well established methodology from the information retrieval field

mathematical treatment of context effects in phoneme and word recognition percent recognition of phonemes and whole syllables measured in both consonant vowel consonant cvc words and cvc nonsense syllables is reported for normal young adults listening at four signal to noise s n ratios similar data are reported for the recognition of words and whole sentences in three types of sentence high predictability hp sentences with both semantic and syntactic constraints low predictability lp sentences with primarily syntactic constraints and zero predictability zp sentences with neither semantic nor syntactic constraints the probability of recognition of speech units in context pc is shown to be related to the probability of recognition without context pi by the equation pc 1 1 pi k where k is a constant the factor k is interpreted as the amount by which the channels of statistically independent information are effectively multiplied when contextual constraints are added empirical values of k are approximately 1 3 and 2 7 for word and sentence context respe

estimating the parameters of exponentially damped sinusoids and pole zero modeling in noise we have presented techniques 1 6 based on linear prediction lp and singular value decomposition svd for accurate estimation of closely spaced frequencies of sinusoidal signals in noise in this note we extend these techniques to estimate the parameters of exponentially damped sinusoidal signals in noise the estimation procedure presented here makes use of backward prediction in addition to svd first the method is applied to data consisting of one and two exponentially damped sinusoids the choice of one and two signal components facilitates the comparison of estimation error in pole damping factors and pole frequencies to the appropriate cramer rao cr bounds and to traditional methods of linear prediction second our method is applied to an example due to steiglitz 8 in which the data consists of noisy values of the impulse response samples composed of many exponentially damped sinusoids of a linear system having both poles and zeros the poles of the system are accurately determined by our method and the zeros are obtained subsequently using shanks method

robust automatic selection of optimal views in multi view free form object recognition this paper addresses the issue of automatic selection of the best and the optimum number of representative views for each object in a database that can enable the accurate recognition of that object from any single arbitrary view of the object the object boundary in each view is represented by its curvature scale space css image the css representation has been selected for mpeg 7 standardisation as a contour shape descriptor the paper also presents a novel method for fusion of results from combined shape descriptors the utilisation of this method for multi view three dimensional 3 d object recognition has been explored the object boundary of each view is represented effectively using the css technique moment invariants and fourier descriptors it has been shown that the results obtained from the fusion method are superior to the results obtained from any single technique the method has been tested on a collection of free form 3 d objects each object has been modelled using an optimal number of silhouette contours obtained from different viewpoints this number varies depending on the complexity of the object and the measure of expected accuracy a comprehensive analysis of the performance of the system has been given

statistical shape analysis clustering learning and testing using a differential geometric treatment of planar shapes we present tools for 1 hierarchical clustering of imaged objects according to the shapes of their boundaries 2 learning of probability models for clusters of shapes and 3 testing of newly observed shapes under competing probability models clustering at any level of hierarchy is performed using a minimum variance type criterion and a markov process statistical means of clusters provide shapes to be clustered at the next higher level thus building a hierarchy of shapes using finite dimensional approximations of spaces tangent to the shape space at sample means we implicitly impose probability models on the shape space and results are illustrated via random sampling and classification hypothesis testing together hierarchical clustering and hypothesis testing provide an efficient framework for shape retrieval examples are presented using shapes and images from eth surrey and amcom databases

benefit of high rate envelope cues in vocoder processing effect of number of channels and spectral region in cochlear implants or vocoder simulations of cochlear implants the transmission of envelope cues at high rates related to voice fundamental frequency f0 may be limited by the widths of the filters used to form the channels and or by the cutoff frequency flp of the low pass filters used for envelope extraction the effect of varying flp in tone and noise vocoders was investigated for channel numbers n from 6 to 18 as n increased the widths of the channels decreased the value of flp was 45hz envelope or e filter or 180hz pitch or p filter the following combinations of cutoff frequencies were used for channels below and above 1500hz respectively ee pe ep and pp results from a competing talker task showed that the tone vocoder led to better intelligibility than the noise vocoder the pp condition led to the best intelligibility and the ee condition to the worst for n 6 intelligibility was better for condition pe than for condition ep for n 18 the reverse was true the results

perceptually relevant and piecewise linear matching of silhouettes in this paper a novel alignment method for silhouettes is proposed this method is based on the establishment of correspondences between landmarks on their boundaries and in turn on the establishment of correspondences of the boundary pieces in between these landmarks the method yields more correct correspondences than conventional methods that scale the arc length descriptions of silhouettes to align them the selection of landmarks is investigated as to the robustness of their localization and their perceptual relevance matching of silhouettes is then achieved by quantifying the dissimilarity of a pair of silhouette boundaries based on a novel dissimilarity metric the matching procedure is evaluated based on retrieval experiments and it is concluded that the precision of the results is higher than that obtained by conventional pointwise comparison methods

silhouette based isolated object recognition through curvature scale space a complete fast and practical isolated object recognition system has been developed which is very robust with respect to scale position and orientation changes of the objects as well as noise and local deformations of shape due to perspective projection segmentation errors and non rigid material used in some objects the system has been tested on a wide variety of three dimensional objects with different shapes and material and surface properties a light box setup is used to obtain silhouette images which are segmented to obtain the physical boundaries of the objects which are classified as either convex or concave convex curves are recognized using their four high scale curvature extrema points curvature scale space css representations are computed for concave curves the css representation is a multi scale organization of the natural invariant features of a curve curvature zero crossings or extrema and useful for very reliable recognition of the correct model since it places no constraints on the shape of objects a three stage coarse to fine matching algorithm prunes the search space in stage one by applying the css aspect ratio test the maxima of contours in css representations of the surviving models are used for fast css matching in stage two finally stage three verifies the best match and resolves any ambiguities by determining the distance between the image and model curves transformation parameter optimization is then used to find the best fit of the input object to the correct model

polygonal approximation of digital planar curves through break point suppression this paper presents a new algorithm that detects a set of dominant points on the boundary of an eight connected shape to obtain a polygonal approximation of the shape itself the set of dominant points is obtained from the original break points of the initial boundary where the integral square is zero for this goal most of the original break points are deleted by suppressing those whose perpendicular distance to an approximating straight line is lower than a variable threshold value the proposed algorithm iteratively deletes redundant break points until the required approximation which relies on a decrease in the length of the contour and the highest error is achieved a comparative experiment with another commonly used algorithm showed that the proposed method produced efficient and effective polygonal approximations for digital planar curves with features of several sizes

pose estimation by fusing noisy data of different dimensions a method for fusing and integrating different 2d and 3d measurements for pose estimation is proposed the 2d measured data is viewed as 3d data with infinite uncertainty in particular directions the method is implemented using kalman filtering it is robust and easily parallelizable

consonant recognition loss in hearing impaired listeners this paper presents a compact graphical method for comparing the performance of individual hearing impaired hi listeners with that of an average normal hearing nh listener on a consonant by consonant basis this representation named the consonant loss profile clp characterizes the effect of a listener s hearing loss on each consonant over a range of performance the clp shows that the consonant loss which is the signal to noise ratio snr difference at equal nh and hi scores is consonant dependent and varies with the score this variation in the consonant loss reveals that hearing loss renders some consonants unintelligible while it reduces noise robustness of some other consonants the conventional snr loss metric snr50 defined as the snr difference at 50 recognition score is insufficient to capture this variation the snr50 value is on average 12 db lower when measured with sentences using standard clinical procedures than when measured with nonsense syllables a listener with symmetric hearing loss may not have identical clps for both ears some consonant confusions by hi listeners are influenced by the high frequency hearing loss even at a presentation level as high as 85 db sound pressure level

speech reception by listeners with real and simulated hearing impairment effects of continuous and interrupted noise the effects of audibility and age on masking for sentences in continuous and interrupted noise were examined in listeners with real and simulated hearing loss the absolute thresholds of each of ten listeners with sensorineural hearing loss were simulated in normal hearing listeners through a combination of spectrally shaped threshold noise and multi band expansion for octave bands with center frequencies from 0 25 8 khz each individual hearing loss was simulated in two groups of three normal hearing listeners an age matched and a non age matched group the speech to noise ratio s n for 50 correct identification of hearing in noise test hint sentences was measured in backgrounds of continuous and temporally modulated 10 hz square wave noise at two overall levels for unprocessed speech and for speech that was amplified with the nal rp prescription the s n in both continuous and interrupted noise of the hearing impaired listeners was relatively well simulated in both groups of normal hearing listeners thus release from masking the difference in s n obtained in continuous versus interrupted noise appears to be determined primarily by audibility minimal age effects were observed in this small sample observed values of masking release were compared to predictions derived from intelligibility curves generated using the extended speech intelligibility index esii rhebergen et al 2006 j acoust soc am 120 3988 3997

shape indexing using self organizing maps in this paper we propose a novel approach to generate the topology preserving mapping of structural shapes using self organizing maps soms the structural information of the geometrical shapes is captured by relational attribute vectors these vectors are quantised using an som using this som a histogram is generated for every shape these histograms are treated as inputs to train another som which yields a topology preserving mapping of the geometric shapes by appropriately choosing the relational vectors it is possible to generate a mapping that is invariant to some chosen transformations such as rotation translation scale affine or perspective transformations experimental results using trademark objects are presented to demonstrate the performance of the proposed methodology

image retrieval based on shape similarity by edge orientation autocorrelogram abstract this paper introduces a new feature vector for shape based image indexing and retrieval this feature classifies image edges based on two factors their orientations and correlation between neighboring edges hence it includes information of continuous edges and lines of images and describes major shape properties of images this scheme is effective and robustly tolerates translation scaling color illumination and viewing position variations experimental results show superiority of proposed scheme over several other indexing methods averages of precision and recall rates of this new indexing scheme for retrieval as compared with traditional color histogram are 1 99 and 1 59 times respectively these ratios are 1 26 and 1 04 compared to edge direction histogram

on the number of channels needed to understand speech recent studies have shown that high levels of speech understanding could be achieved when the speech spectrum was divided into four channels and then reconstructed as a sum of four noise bands or sine waves with frequencies equal to the center frequencies of the channels in these studies speech understanding was assessed using sentences produced by a single male talker the aim of experiment 1 was to assess the number of channels necessary for a high level of speech understanding when sentences were produced by multiple talkers in experiment 1 sentences produced by 135 different talkers were processed through n 2 n 16 number of channels synthesized as a sum of n sine waves with frequencies equal to the center frequencies of the filters and presented to normal hearing listeners for identification a minimum of five channels was needed to achieve a high level 90 of speech understanding asymptotic performance was achieved with eight channels at least for the speech material used in this study the outcome of experiment 1 demonstrated that the number of channels needed to reach asymptotic performance varies as a function of the recognition task and or need for listeners to attend to fine phonetic detail in experiment 2 sentences were processed through 6 and 16 channels and quantized into a small number of steps the purpose of this experiment was to investigate whether listeners use across channel differences in amplitude to code frequency information particularly when speech is processed through a small number of channels for sentences processed through six channels there was a significant reduction in speech understanding when the spectral amplitudes were quantized into a small number 8 of steps high levels 92 of speech understanding were maintained for sentences processed through 16 channels and quantized into only 2 steps the findings of experiment 2 suggest an inverse relationship between the importance of spectral amplitude resolution number of steps and spectral resolution number of channels

efficient adaptive procedures for threshold and concurrent slope estimates for psychophysics and speech intelligibility tests the minimum standard deviations achievable for concurrent estimates of thresholds and psychometric function slopes as well as the optimal target values for adaptive procedures are calculated as functions of stimulus level and track length on the basis of the binomial theory the optimum pair of targets for a concurrent estimate is found at the correct response probabilities p1 0 19 and p2 0 81 for the logistic psychometric function an adaptive procedure that converges at these optimal targets is introduced and tested with monte carlo simulations the efficiency increases rapidly when each subject s response consists of more than one statistically independent bernoulli trial sentence intelligibility tests provide more than one bernoulli trial per sentence when each word is scored separately the number of within sentence trials can be quantified by the j factor boothroyd and nittrouer j acoust soc am 84 101 114 1988 the adaptive procedure was evaluated with 10 normal hearing and 11 hearing imp

shape similarity retrieval under affine transforms the maxima of curvature scale space css image have already been used to represent 2 d shapes in different applications the representation has shown robustness under the similarity transformations scaling orientation changes translation and even noise can be easily handled by the representation and its associated matching algorithm in this paper we examine the robustness of the representation under general affine transforms we have a database of 1100 images of marine creatures the contours in this database demonstrate a great range of shape variation a database of 5000 contours has been constructed using 500 real object boundaries and 4500 contours which are the affine transformed versions of real objects the css representation is then used to find similar shapes from this prototype database the results provide substantial evidence of stability of the css image and its contour maxima under affine transformation the method is also evaluated objectively through a large classified database and its performance is compared with the performance of two well known methods namely fourier descriptors and moment invariants the css shape descriptor has been selected for mpeg 7 standardization

using statistical decision theory to predict speech intelligibility iii effect of audibility on speech recognition sensitivity the speech recognition sensitivity srs model h musch and s buus j acoust soc am 109 2896 2909 2001 is a macroscopic model for predicting speech intelligibility the present study proposes a modification to the relation between the srs model s audibility noise variance and the signal excitation to noise excitation ratio snre in the auditory periphery the modified relation is derived from data obtained in nine studies that measured normal hearing listeners consonant recognition performance at several levels of speech spectrum shaped noise when the audibility noise variance is directly proportional to the relative power of the noise excitation in the auditory periphery the srs model yields good predictions of the data four of the nine studies also reported consonant recognition performance in various filtering conditions good predictions of these data were achieved with srs model parameters that were consistent with the model parameters fitting the speech in noise data and with the mode

an affine invariant curve matching method for photo identification of marine mammals individual identification of marine mammals is of interest to marine biologists this paper aims at the recognition of the edges associated with marine mammals whose pictures are taken under affine transformations the introduced affine curve matching method uses the area of mismatch between a query and a database curve this area is obtained by optimally aligning the curves based on the minimum affine distance involving their distinguishing points the method is applied to databases of sea lions gray whales and dolphins and its performance is compared with two other affine curve matching methods the results show that the introduced curve matching approach outperforms the other approaches and thus further reduces the search time for identifying an individual the developed method is of general purpose as it can be used for other affine curve matching applications

phoneme recognition in vocoded maskers by normal hearing and aided hearing impaired listeners this study compared modulation benefit for phoneme recognition obtained by normal hearing nh and aided hearing impaired hi listeners consonant and vowel recognition scores were measured using nonsense syllables in the presence of a steady state noise and four vocoded speech maskers vocoded maskers were generated by modulating the steady state noise in either one or six frequency channels with the speech envelope extracted from the speech of either a single talker or a four talker babble aided hi listeners obtained lower consonant recognition scores than nh listeners in all masker conditions vowel recognition scores for aided hi listeners were comparable to nh scores except in the six channel vocoded masker conditions where they were relatively lower analysis using the extended speech intelligibility index developed by rhebergen versfeld and dreschler 2006 j acoust soc am 120 6 3988 3997 suggested that the signal to noise ratio deficit observed in aided hi listeners was largely due to uncompensated audibility loss there was no significant difference between modulation masking release obtained by nh and aided hi listeners for both consonant and vowel recognition

automated parameter identification and order reduction for discrete time series models the estimated models are used to predict the transient response of structures subject to arbitrary input the linear structural transfer function is expressed in the form of an arma discrete time series model overspecification of the system order has proven useful in reducing the bias errors but the resulting model may be excessively large and will contain noise related modes

evaluation of context effects in sentence recognition it was investigated whether the model for context effects developed earlier by bronkhorst et al j acoust soc am 93 499 509 1993 can be applied to results of sentence tests used for the evaluation of speech recognition data for two german sentence tests that differed with respect to their semantic content were analyzed they had been obtained from normal hearing listeners using adaptive paradigms in which the signal to noise ratio was varied it appeared that the model can accurately reproduce the complete pattern of scores as a function of signal to noise ratio both sentence recognition scores and proportions of incomplete responses in addition it is shown that the model can provide a better account of the relationship between average word recognition probability pew and sentence recognition probability pw than the relationship pw pej which has been used in previous studies analysis of the relationship between j and the model parameters shows that j is nevertheless a very useful parameter especially when it is combined with the parameter j which can be derived using the equivalent relationship pw 0 l pe j where pw 0 is the probability of recognizing none of the words in the sentence these parameters not only provide complementary information on context effects present in the speech material but they also can be used to estimate the model parameters because the model can be applied to both speech and printed text an experiment was conducted in which part of the sentences was presented orthographically with 1 3 missing words the results revealed a large difference between the values of the model parameters for the two presentation modes this is probably due to the fact that with speech subjects can reduce the number of alternatives for a certain word using partial information that they have perceived i e not only using the sentence context a method for mapping model parameters from one mode to the other is suggested but the validity of this approach has to be confirmed with additional data 2002 acoustical society of america

on image analysis by the methods of moments various types of moments have been used to recognize image patterns in a number of applications a number of moments are evaluated and some fundamental questions are addressed such as image representation ability noise sensitivity and information redundancy moments considered include regular moments legendre moments zernike moments pseudo zernike moments rotational moments and complex moments properties of these moments are examined in detail and the interrelationships among them are discussed both theoretical and experimental results are presented

within consonant perceptual differences in the hearing impaired ear the consonant recognition of 17 ears with sensorineural hearing loss is evaluated for 14 consonants p t k f s b d g v z m n under four speech weighted noise conditions 0 6 12 db snr quiet one male and one female talker were chosen for each consonant resulting in 28 total consonant vowel test tokens for a given consonant tokens by different talkers were observed to systematically differ in both the robustness to noise and or the resulting confusion groups such within consonant token differences were observed for over 60 of the tested consonants and all hi ears only when hi responses are examined on an individual token basis does one find that the error may be limited to a small subset of tokens with confusion groups that are restricted to fewer than three confusions on average averaging different tokens of the same consonant can raise the entropy of a listener s responses i e the size of the confusion group causing the listener to appear to behave in a less systematic way quantifying these token differences provides insight into hi perception of speech under noisy conditions and characterizes each listener s hearing impairment

importance of tonal envelope cues in chinese speech recognition recent studies have shown that temporal waveform envelope cues can provide significant information for english speech recognition this study investigated the use of temporal envelope cues in a tonal language mandarin chinese in this study the speech was divided into several frequency analysis bands the amplitude envelope was extracted from each band by half wave rectification and low pass filtering and was used to modulate a noise of the same bandwidth as the analysis band these manipulations preserved temporal and amplitude cues in each frequency band but removed the spectral detail within each band chinese vowels consonants tones and sentences were identified by 12 native chinese speaking listeners with 1 2 3 and 4 noise bands the results showed that the recognition score of vowels consonants and sentences increased monotonically with the number of bands a pattern similar to that observed in english speech recognition in contrast tones were consistently recognized at about 80 correct level independent of the number of bands this high level of tone recognition produced a significant difference in the open set sentence recognition between chinese 11 0 and english 2 9 for the one band condition where no spectral information was available the data also revealed that with primarily temporal cues the falling rising tone tone 3 and the falling tone tone 4 were more easily recognized than the flat tone tone 1 and the rising tone tone 2 this differential pattern in tone recognition resulted in a similar pattern in word recognition words having either tone 3 or 4 were more likely to be recognized while words having tone 1 and 2 were not the quantitative role of tones in chinese speech recognition was further explored using a power function model and found to play a significant role in relating phoneme recognition to sentence recognition

the effect of smoothing filter slope and spectral frequency on temporal speech information it is known that information contained within the filter skirts can provide cues important to speech intelligibility however the role of filter slope during temporal smoothing has received little attention in experiment 1 smoothing filter slope angle was found to have a large effect on the intelligibility of sentences represented by three amplitude modulated sinusoids in experiment 2 the use of temporal cues above 16hz was examined across various regions of the spectrum when increases in rate were presented to individual spectral bands intelligibility only increased when presented in the higher spectral region this result suggests a greater reliance on higher rate cues in this region however intelligibility was greatest when these cues were distributed across the spectrum indicating that their effective use is not restricted solely to this region

identification of modal parameters from measured output data using vector backward autoregressive model in this paper a modal identification system that is based on the vector backward autoregressive vbar model has been developed for the identification of natural frequencies damping ratios and mode shapes of structures from measured output data the modal identification using forward autoregressive approach has some problems in discriminating the structure modes from spurious modes on the contrary the vbar approach provides a determinate boundary for the separation of system modes from spurious modes and an eigenvalue filter for the selection of physical modes is existent in the proposed method for convenience of application the backward state equation established from vbar model is transformed into a forward state equation which is termed as transformed vfar model in this paper in addition the extraction of equivalent system matrix of state equation of motion for structures from the transformed vfar model has been developed and then the normal modes can be calculated from the identified equivalent system matrix two examples of modal identification are carried out to demonstrate the availability and effectiveness of the proposed backward approach 1 numerical modal identification for a three degree of freedom dynamic system with noise level in 20 of r m s of measured output data 2 experimental modal identification of a cantilever beam finally to show the advantage of the proposed vbar approach on the selection of physical modes the modal identification by stochastic subspace method was performed the results from both methods are compared

features of stimulation affecting tonal speech perception implications for cochlear prostheses tone languages differ from english in that the pitch pattern of a single syllable word conveys lexical meaning in the present study dependence of tonal speech perception on features of the stimulation was examined using an acoustic simulation of a cis type speech processing strategy for cochlear prostheses contributions of spectral features of the speech signals were assessed by varying the number of filter bands while contributions of temporal envelope features were assessed by varying the low pass cutoff frequency used for extracting the amplitude envelopes ten normal hearing native mandarin chinese speakers were tested when the low pass cutoff frequency was fixed at 512 hz consonant vowel and sentence recognition improved as a function of the number of channels and reached plateau at 4 to 6 channels subjective judgments of sound quality continued to improve as the number of channels increased to 12 the highest number tested tone recognition i e recognition of the four mandarin tone patterns depended on both the number of channels and the low pass cutoff frequency the trade off between the temporal and spectral cues for tone recognition indicates that temporal cues can compensate for diminished spectral cues for tone recognition and vice versa an additional tone recognition experiment using syllables of equal duration showed a marked decrease in performance indicating that duration cues contribute to tone recognition a third experiment showed that recognition of processed fm patterns that mimic mandarin tone patterns was poor when temporal envelope and duration cues were removed

a theory of multiscale curvature based shape representation for planar curves a shape representation technique suitable for tasks that call for recognition of a noisy curve of arbitrary shape at an arbitrary scale or orientation is presented the method rests on the describing a curve at varying levels of detail using features that are invariant with respect to transformations that do not change the shape of the curve three different ways of computing the representation are described they result in three different representations the curvature scale space image the renormalized curvature scale space image and the resampled curvature scale space image the process of describing a curve at increasing levels of abstraction is referred to as the evolution or arc length evolution of that curve several evolution and arc length evolution properties of planar curves are discussed

shape codification indexing and retrieval using the quad tree structure the author presents in this paper a new approach for indexing and content based image retrieval based on the quad tree structure the 3d objects are represented by their silhouettes and codified following the filling rate of each quadrant at different levels of the quad tree subdivision the author proposes a modified linear codification for silhouettes this method improves the processing time because in opposite to the traditional algorithms the author s algorithm has not a processing time that is proportional to the number of pixels in the image as the same descriptor may characterize a set of different shapes the author proposes also efficient similarity measures to distinguish different objects having the same index in order to apply the approach to the retrieval process