971 resultados para call centers


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The use of the PC and Internet for placing telephone calls will present new opportunities to capture vast amounts of un-transcribed speech for a particular speaker. This paper investigates how to best exploit this data for speaker-dependent speech recognition. Supervised and unsupervised experiments in acoustic model and language model adaptation are presented. Using one hour of automatically transcribed speech per speaker with a word error rate of 36.0%, unsupervised adaptation resulted in an absolute gain of 6.3%, equivalent to 70% of the gain from the supervised case, with additional adaptation data likely to yield further improvements. LM adaptation experiments suggested that although there seems to be a small degree of speaker idiolect, adaptation to the speaker alone, without considering the topic of the conversation, is in itself unlikely to improve transcription accuracy.

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The most common daily trip for employed persons and students is the commute to and from work and/or place of study. Though there are clear environmental, health and safety benefits from using public transport instead of private vehicles for these trips, a high proportion of commuters still choose private vehicles to get to work or study. This study reports an investigation of psychological factors influencing students’ travel choices from the perspective of the Theory of Planned Behaviour (TPB). Students from 3 different university campuses (n= 186) completed a cross-sectional survey on their car commuting behaviour. Particular focus was given to whether car commuting habits could add to understanding of commuting behaviour over and above behavioural intentions. Results indicated that, as expected, behavioural intention to travel by car was the strongest TPB predictor of car commuting behaviour. Further, general car commuting habits explained additional variance over and above TPB constructs, though the contribution was modest. No relationship between habit and intentions was found. Overall results suggest that, although student car commuting behaviour is habitual in nature, it is predominantly guided by reasoned action. Implications of these findings are that in order to alter the use of private vehicles, the factors influencing commuters’ intentions to travel by car must be addressed. Specifically, interventions should target the perceived high levels of both the acceptability of commuting by car and the perceived control over the choice to commute by car.

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Visiting a modern shopping center is becoming vital in our society nowadays. The fast growth of shopping center, transportation system, and modern vehicles has given more choices for consumers in shopping. Although there are many reasons for the consumers in visiting the shopping center, the influence of travel time and size of shopping center are important things to be considered towards the frequencies of visiting customers in shopping centers. A survey to the customers of three major shopping centers in Surabaya has been conducted to evaluate the Ellwood’s model and Huff’s model. A new exponent value N of 0.48 and n of 0.50 has been found from the Ellwood’s model, while a coefficient of 0.267 and an add value of 0.245 have been found from the Huff’s model.

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Sustainable practices are more than ever on the radar screen of organizations, triggered by a growing demand of the wider population towards approaches and practices that can be considered "green" or "sustainable". Our specific intent with this call for action is to immerse deeper into the role of business processes, and specifically the contributions that the management of these processes can play in leveraging the transformative power of information systems (IS) in order to create environmentally sustainable organizations. Our key premise is that business and information technology (IT) managers need to engage in a process-focused discussion to enable a common, comprehensive understanding of process, and the process-centered opportunities for making these processes, and ultimately the organization as a process-centric entity, "green". Based on a business process lifecycle model, we propose possible avenues for future research.

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Schools have long been seen as institutions for preparing children for life, both academically and as moral agents in society. In order to become capable, moral citizens, children need to be provided with opportunities to learn moral values. However, little is known about how teachers enact social and moral values programs in the classroom. The aim of this paper is to investigate the practices that Australian early years teachers describe as important for teaching moral values. To investigate early years teachers’ understandings of moral pedagogy, 379 Australian teachers with experience teaching children in the early years were invited to participate in an on-line survey. This paper focuses on responses provided to an open-ended question relating to teaching practices for moral values. The responses were analysed using an interpretive methodology. The results indicate that the most prominent approaches to teaching moral values described by this group of Australian early years teachers were engaging children in moral activities. This was closely followed by teaching practices for transmitting moral values. Engaging children in building meaning and participatory learning for moral values were least often described.

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This paper presents an extensive review on the services, six-sigma, and application of six-sigma in services. In order to improve service quality focus on service process is necessary. Six-sigma is a philosophy which also concentrates on the improvement of process. So, six-sigma if properly applied can be useful for services. This study focuses on the application aspect of six-sigma to wider range of services. The wider applicability of six-sigma depends on identification of key performance indicators(KPIs) for different types of service processes. A case study is conducted in call center services to identify, analyze and compare critical to quality characteristics (CTQs) and KPIs with other types of services available in literature. This study will be helpful to both practitioners and researchers.

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Travel writing published by Swamp : A Journal of Post-graduate Creative Writing.

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Monitoring the natural environment is increasingly important as habit degradation and climate change reduce theworld’s biodiversity.We have developed software tools and applications to assist ecologists with the collection and analysis of acoustic data at large spatial and temporal scales.One of our key objectives is automated animal call recognition, and our approach has three novel attributes. First, we work with raw environmental audio, contaminated by noise and artefacts and containing calls that vary greatly in volume depending on the animal’s proximity to the microphone. Second, initial experimentation suggested that no single recognizer could dealwith the enormous variety of calls. Therefore, we developed a toolbox of generic recognizers to extract invariant features for each call type. Third, many species are cryptic and offer little data with which to train a recognizer. Many popular machine learning methods require large volumes of training and validation data and considerable time and expertise to prepare. Consequently we adopt bootstrap techniques that can be initiated with little data and refined subsequently. In this paper, we describe our recognition tools and present results for real ecological problems.

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Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches to the virtual machine placement problem consider the energy consumption by physical machines in a data center only, but do not consider the energy consumption in communication network in the data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement in order to make the data center more energy-efficient. In this paper, we propose a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both the servers and the communication network in the data center. Experimental results show that the genetic algorithm performs well when tackling test problems of different kinds, and scales up well when the problem size increases.