A comparative analysis of major ERP lifecycle implementation, management and support issues in Queensland Government

This paper reports on a study of ERP lifecycle major issues from the perspectives of individuals with substantial and diverse involvement with SAP Financials in Queensland Government. A survey was conducted of 117 ERP system project participants in five closely related state government agencies. A modified Delphi technique identified, rationalized and weighed perceived major issues in ongoing ERP life cycle implementation, management and support. The five agencies each implemented SAP Financials simultaneously using a common implementation partner. The three survey rounds of the Delphi technique, together with coding and synthesizing procedures, resulted in a set of 10 major issue categories with 38 sub-issues. Relative scores of issue importance are compared across government agencies, roles (client vs implementation partner) and organizational levels (strategic, technical and operational). Study findings confirm the importance of this finer partitioning of the data, and distinctions identified reflect the circumstances of ERP lifecycle implementation, management and support among the stakeholder groups. The study findings should also be of interest to stakeholders who seek to better understand the issues surrounding ERP systems and to better realise the benefits of ERP.

Likelihood-maximising frameworks for enhanced in-car speech recognition

Speech recognition in car environments has been identified as a valuable means for reducing driver distraction when operating non-critical in-car systems. Likelihood-maximising (LIMA) frameworks optimise speech enhancement algorithms based on recognised state sequences rather than traditional signal-level criteria such as maximising signal-to-noise ratio. Previously presented LIMA frameworks require calibration utterances to generate optimised enhancement parameters which are used for all subsequent utterances. Sub-optimal recognition performance occurs in noise conditions which are significantly different from that present during the calibration session - a serious problem in rapidly changing noise environments. We propose a dialog-based design which allows regular optimisation iterations in order to track the changing noise conditions. Experiments using Mel-filterbank spectral subtraction are performed to determine the optimisation requirements for vehicular environments and show that minimal optimisation assists real-time operation with improved speech recognition accuracy. It is also shown that the proposed design is able to provide improved recognition performance over frameworks incorporating a calibration session.

Diversity of accuracy profiles for absolute pitch recognition

Most advanced musicians are able to identify and label a heard pitch if given an opportunity to compare it to a known reference note. This is called ‘relative pitch’ (RP). A much rarer skill is the ability to identify and label a heard pitch without the need for a reference. This is colloquially referred to as ‘perfect pitch’, but appears in the academic literature as ‘absolute pitch’ (AP). AP is considered by many as a remarkable skill. As people do not seem able to develop it intentionally, it is generally regarded as innate. It is often seen as a unitary skill and that a set of identifiable criteria can distinguish those who possess the skill from those who do not. However, few studies have interrogated these notions. The present study developed and applied an interactive computer program to map pitch-labelling responses to various tonal stimuli without a known reference tone available to participants. This approach enabled the identification of the elements of sound that impacted on AP. Pitch-labelling responses of 14 participants with AP were recorded for their accuracy. Each participant’s response to the stimuli was unique. Their accuracy of labelling varied across dimensions such as timbre, range and tonality. The diversity of performance between individuals appeared to reflect their personal musical experience histories.