varunr14/newsummary huggingface dataset:
Due to the increasing aging population in modern society and to the proliferation of smart devices there is a need to enhance speech recognition among smart devices in order to make information easily accessible to the elderly as it is to the younger population . In general speech recognition systems are optimized to an average adult s voice and tend to exhibit a lower accuracy rate when recognizing an elderly person s voice due to the effects of speech articulation and speaking style . Additional costs are bound to be incurred when adding modifications to current speech recognitions systems for better speech recognition among elderly users . Thus using a preprocessing application on a smart device can not only deliver better speech recognition but also substantially reduce any added costs . Audio samples of 50 words uttered by 80 elderly and young adults were collected and comparatively analyzed . The speech patterns of the elderly have a slower speech rate with longer inter syllabic silence length and slightly lower speech intelligibility . The speech recognition rate for elderly adults could be improved by means of increasing the speech rate adding a 1.5 increase in accuracy eliminating silence periods adding another 4.2 increase in accuracy and boosting the energy of the formant frequency bands for a 6 boost in accuracy . After all the preprocessing a 12 increase in the accuracy of elderly speech recognition was achieved . Through this study we show that speech recognition of elderly voices can be improved through modifying specific aspects of differences in speech articulation and speaking style . In the future we will conduct studies on methods that can precisely measure and adjust speech rate and find additional factors that impact intelligibility . 


Summary: Preprocessed elderly voice signals were tested with an android smart phone. Speech recognition accuracy increased to 1.5 by increasing the speech rate. Speech recognition accuracy increased to 4.2 by eliminating intersyllabic pauses. Speech recognition accuracy increased to 6 by boosting formant frequency bands. After all the preprocessing 12 increase in the recognition accuracy was achieved.
This work presents a conceptually simple experiment consisting of a cantilever beam with a nonlinear spring at the tip . The configuration allows manipulation of the relative spacing between the modal frequencies of the underlying linear structure and this permits the deliberate introduction of internal resonance . A 3 1 resonance is studied in detail the response around the first mode shows a classic stiffening response with the addition of more complex dynamic behaviour and an isola region . Quasiperiodic responses are also observed but in this work the focus remains on periodic responses . Predictions using Normal Form analysis and continuation methods show good agreement with experimental observations . The experiment provides valuable insight into frequency responses of nonlinear modal structures and the implications of nonlinearity for vibration tests . Young s modulus vector of Fourier components of the forcing signal nth modal variable first modal response amplitude taken at drive frequency second modal response amplitude taken at third harmonic of drive frequency vector of Fourier components of the voltage signal sent to the shaker amplifier resonant component of the nth modal variable response amplitude of u axial coordinate lateral coordinate linear modal damping ratio phase Poisson s ratio mass density nth mode shape function shorthand for linear natural angular frequency of nth mode resonant response frequency of nth modal variable 


Summary: Experimental demonstration of 3 1 internal resonance in an easy to reproduce structure with transparent underlying physics. Experimental demonstration of isolated region in frequency response. Normal forms backbone analysis of the free structure used to explain the rich dynamics seen. Reasonable match with continuation analysis in AUTO the revealed structure of bifurcations sheds further light on the response of the forced and damped system.
For acquiring new skills or knowledge contemporary learners frequently rely on the help of educational technologies supplementing human teachers as a learning aid . In the interaction with such systems speech based communication between the human user and the technical system has increasingly gained importance . Since spoken computer output can take on a variety of forms depending on the method of speech generation and the employment of prosodic modulations the effects of such auditory variations on the user s learning achievement require systematic investigation . The experiment reported here examined the specific effects of speech generation method and prosody of spoken system feedback in a computer supported learning environment and may serve as validational tool for future investigations of spoken computer feedback effects on learning . Learning performance in a basic cognitive task was compared between users receiving pre recorded naturally spoken system feedback with neutral prosody pre recorded feedback with motivating prosody or computer synthesized feedback . The observed results provide empirical evidence that users of technical tutoring systems benefit from pre recorded naturally spoken feedback and do even more so from feedback with motivational prosodic modulations matching their performance success . Theoretical implications and considerations for future implementations of spoken feedback in computer based educational systems are discussed . 


Summary: Users of tutorial systems are affected by auditory modulations in system feedback. Users learn faster with naturally spoken than with synthesized computer feedback. Users learning rates benefit from system feedback with motivational prosody.
There has been much debate surrounding the potential benefits and costs of online interaction . The present research argues that engagement with online discussion forums can have underappreciated benefits for users well being and engagement in offline civic action and that identification with other online forum users plays a key role in this regard . Users of a variety of online discussion forums participated in this study . We hypothesized and found that participants who felt their expectations had been exceeded by the forum reported higher levels of forum identification . Identification in turn predicted their satisfaction with life and involvement in offline civic activities . Formal analyses confirmed that identification served as a mediator for both of these outcomes . Importantly whether the forum concerned a stigmatized topic moderated certain of these relationships . Findings are discussed in the context of theoretical and applied implications . 


Summary: Online discussion forums have benefits at individual and society level. They are positively linked to well being for stigmatised group members. Online discussion forum use is linked to offline civic engagement in related areas. Identification with other forum users mediates the above relationships. Online discussion forums are of greater applied importance than has been realized.
This paper regards social question and answer collections such as Yahoo Answers as knowledge repositories and investigates techniques to mine knowledge from them to improve sentence based complex question answering systems . Specifically we present a question type specific method that extracts question type dependent cue expressions from social Q A pairs in which the question types are the same as the submitted questions . We compare our approach with the question specific and monolingual translation based methods presented in previous works . The question specific method extracts question dependent answer words from social Q A pairs in which the questions resemble the submitted question . The monolingual translation based method learns word to word translation probabilities from all of the social Q A pairs without considering the question or its type . Experiments on the extension of the NTCIR 2008 Chinese test data set demonstrate that our models that exploit social Q A collections are significantly more effective than baseline methods such as LexRank . The performance ranking of these methods is QTSM QSM MTM . The largest F3 improvements in our proposed QTSM over QSM and MTM reach 6.0 and 5.8 respectively . 


Summary: The proposed approach leverages social Q A collections to improve automatic complex QA system. There is no need to manually collect training Q A pairs that are necessary for supervised machine learning approaches. Extensive comparison experiments are conducted i.e. LexRank question specific and translation based approaches are compared. Experiments on the extension of NTCIR 2008 test questions indicate that the proposed approach is more effective.
The increasing convergence of the gambling and gaming industries has raised questions about the extent to which social casino game play may influence gambling . This study aimed to examine the relationship between social casino gaming and gambling through an online survey of 521 adults who played social casino games in the previous 12 months . Most social casino game users reported that these games had no impact on how much they gambled . However 9.6 reported that their gambling overall had increased and 19.4 reported that they had gambled for money as a direct result of these games . Gambling as a direct result of social casino games was more common among males younger users those with higher levels of problem gambling severity and more involved social casino game users in terms of game play frequency and in game payments . The most commonly reported reason for gambling as a result of playing social casino games was to win real money . As social casino games increased gambling for some users this suggests that simulated gambling may influence actual gambling expenditure particularly amongst those already vulnerable to or affected by gambling problems . 


Summary: The social casino games and gambling industries and products are converging. 521 adults who played social casino games in the previous 12 months completed an online survey. A minority 19.4 of social casino game players gambled as a result of these games. Gambling was typically motivated by a desire to win money which is not possible in games. Social casino games may increase gambling for some players including those vulnerable to gambling problems.
Pathological speech usually refers to the condition of speech distortion resulting from atypicalities in voice and or in the articulatory mechanisms owing to disease illness or other physical or biological insult to the production system . Although automatic evaluation of speech intelligibility and quality could come in handy in these scenarios to assist experts in diagnosis and treatment design the many sources and types of variability often make it a very challenging computational processing problem . In this work we propose novel sentence level features to capture abnormal variation in the prosodic voice quality and pronunciation aspects in pathological speech . In addition we propose a post classification posterior smoothing scheme which refines the posterior of a test sample based on the posteriors of other test samples . Finally we perform feature level fusions and subsystem decision fusion for arriving at a final intelligibility decision . The performances are tested on two pathological speech datasets the NKI CCRT Speech Corpus and the TORGO database by evaluating classification accuracy without overlapping subjects data among training and test partitions . Results show that the feature sets of each of the voice quality subsystem prosodic subsystem and pronunciation subsystem offer significant discriminating power for binary intelligibility classification . We observe that the proposed posterior smoothing in the acoustic space can further reduce classification errors . The smoothed posterior score fusion of subsystems shows the best classification performance . 


Summary: We propose novel sentence level features to capture atypical variation. Our sentence level features are effective for intelligibility classification. We propose a post classification posterior smoothing scheme. Our smoothing scheme improves classification accuracy of our systems. We test feature level and subsystem fusions for the final intelligibility decision.
This paper describes a noisy channel approach for the normalization of informal text such as that found in emails chat rooms and SMS messages . In particular we introduce two character level methods for the abbreviation modeling aspect of the noisy channel model a statistical classifier using language based features to decide whether a character is likely to be removed from a word and a character level machine translation model . A two phase approach is used in the first stage the possible candidates are generated using the selected abbreviation model and in the second stage we choose the best candidate by decoding using a language model . Overall we find that this approach works well and is on par with current research in the field . 


Summary: Normalization of abbreviations in noisy informal text. Collection filtering and annotation of Twitter status messages. Comparison of statistical and machine translation approaches. Effects of language model order on accuracy. Combination of methods to achieve best results.
Traditional concept retrieval is based on usual word definition dictionaries with simple performance they just map words to their definitions . This approach is mostly helpful for readers and language students but writers sometimes need to find a word that encompasses a set of ideas that they have in mind . For this task inverse dictionaries are ready to help however in some cases a sought word does not correspond to a single definition but to a composite meaning of several concepts . A language producer then tends to require a concept search that starts with a group of words or a series of related terms looking for a target word . This paper aims to assist on this task by presenting a new approach for concept blending through the development of a search by concept method based on vector space representation using semantic analysis and statistical natural language processing techniques . Words are represented as numeric vectors based on different semantic similarity measures and probabilistic measures the semantic properties of a word are captured in the vector elements determined by a given linguistic context . Three different sources are used as context for word vector construction WordNet a distributional thesaurus and the Latent Dirichlet Allocation algorithm each source is used for building a different semantic vector space . The concept blender input is then conformed by a set of n nouns . All input members are read and substituted by their corresponding vectors . Then a semantic space analysis including a filtering and ranking process is carried out to deploy a list of target words . A test set of 50 concepts was created in order to evaluate the system s performance . A group of 30 evaluators found our integrated concept blending model to provide better results for finding an adequate word for the provided set of concepts . 


Summary: A method for merging an arbitrary number of nouns mixing their meanings. Successful model using vector representation scantily explored for concept retrieval. Experiments with 3 semantic space models WN a thesaurus and a topic based model. Good performance with an automatically obtained resource comparable to a manual one. Evaluation by qualified reviewers and comparison with a traditional dictionary.
Living Labs are innovation infrastructures where software companies and research organizations collaborate with lead users to design and develop new products and services . There is not any reference model related to the processes or practices to manage a living lab . This article presents a reference model to manage effectively the synergies of software companies with the other stakeholders participating in a living lab . The article describes the approach used to create the reference model through the analysis of a multiple case study considering six living labs and discusses the lessons learned during the creation of the process reference model . 


Summary: ISO IEC 15504 philosophy helps to formalize effective practices to manage living labs. The PRM covers the absence of a formalized approach to guide living lab management. The reference model contributes to facilitating benchmarking among living labs. The maturity levels provide a feasible path to create and evolve a living lab.
The development of connected mobile applications is a complex task due to device diversity . Therefore device independent approaches are aimed at hiding the differences among the distinct mobile devices in the market . This work proposes DIMAG a software framework to generate connected mobile applications for multiple software platforms following a declarative approach . DIMAG provides transparent data and state synchronization between the server and the client side applications . The proposed platform has been designed making use of existing standards extending them when a required functionality is not provided . 


Summary: The DIMAG framework generates platform independent connected mobile applications. Existing standards were used and refined in the design and implementation of DIMAG. Client server applications are specified in a declarative way. Server side of applications is generated for the Java EE platform. It dynamically generates client applications for Android Java ME and Windows Phone.
Queuing network models provide powerful notations and tools for modeling and analyzing the performance of many different kinds of systems . Although several powerful tools currently exist for solving QNMs some of these tools define their own model representations have been developed in platform specific ways and are normally difficult to extend for coping with new system properties probability distributions or system behaviors . This paper shows how Domain Specific Languages when used in conjunction with Model driven engineering techniques provide a high level and very flexible approach for the specification and analysis of QNMs . We build on top of an existing metamodel for QNMs to define a DSL and its associated tools able to provide a high level notation for the specification of different kinds of QNMs and easy to extend for dealing with other probability distributions or system properties such as system reliability . 


Summary: We have developed an application for specifying and simulating queuing network models. We reuse and extend a de facto standard metamodel for queuing network models PMIF. A modular and easily extensible architecture has been achieved using MDE techniques. The behavior for queuing network models is easily extensible with our approach.
Flexibility maintainability and evolvability are very desirable properties for modern automation control systems . In order to achieve these characteristics modularity is regarded as an important concept in several scientific domains . The reuse of modules facilitates the reproduction of functionality or extensions of existing systems in similar environments . However it is often necessary to prepare such an environment to be able to reuse the intended programmed functionality . In an IEC 61131 3 environment cross vendor reuse of modules is problematic due to dependencies in proprietary programming environments and existing configurations . In this paper we aim to enable cross vendor reuse of modules by controlling these dependencies . Our approach is based on the Normalized Systems Theory from which we derived three guidelines for the design of reusable modules in an IEC 61131 3 environment for automation control projects . These guidelines are intended to support programmers in controlling dependencies regardless of the commercial programming environment they work with . 


Summary: We illustrate that designing cross vendor reusable modules in automation systems is hard. Some theoretical foundations on how to design reusable modules are given. Five dependency problems in IEC 61131 3 projects are illustrated. Three rules are proposed in order to avoid these dependencies.
Food consumption data are collected and used in several fields of science . The data are often combined from various sources and interchanged between different systems . There is however no harmonized and widely used data interchange format . In addition food consumption data are often combined with other data such as food composition data . In the field of food composition successful harmonization has recently been achieved by the European Food Information Resource Network which is now the basis of a standard draft by the European Committee for Standardization . We present an XML based data interchange format for food consumption based on work and experiences related to food composition . The aim is that the data interchange format will provide a basis for wider harmonization in the future . 


Summary: Data interchange format for food consumption data Definition of the key concepts used with food consumption data A generic data model for food consumption data Linking food consumption data with food composition data
A variety of vision ailments are indicated by anomalies in the choroid layer of the posterior visual section . Consequently choroidal thickness and volume measurements usually performed by experts based on optical coherence tomography images have assumed diagnostic significance . Now to save precious expert time it has become imperative to develop automated methods . To this end one requires choroid outer boundary detection as a crucial step where difficulty arises as the COB divides the choroidal granularity and the scleral uniformity only notionally without marked brightness variation . In this backdrop we measure the structural dissimilarity between choroid and sclera by structural similarity index and hence estimate the COB by thresholding . Subsequently smooth COB estimates mimicking manual delineation are obtained using tensor voting . On five datasets each consisting of 97 adult OCT B scans automated and manual segmentation results agree visually . We also demonstrate close statistical match between choroidal thickness distributions obtained algorithmically and manually . Further quantitative superiority of our method is established over existing results by respective factors of 27.67 and 76.04 in two quotient measures defined relative to observer repeatability . Finally automated choroidal volume estimation being attempted for the first time also yields results in close agreement with that of manual methods . 


Summary: Choroid is statistically separated from sclera using structural similarity index. Smoothness in choroid delineation is achieved using tensor voting. Automated choroidal volume estimation is attempted for the first time. Choroidal thickness and volume estimates are given vis vis observer repeatability. Quotients are defined to fairly compare among methods tested on disparate datasets.