A Robust and Efficient Three-Layered Dialogue Component for a Speech-to-Speech Translation System

We present the dialogue component of the speech-to-speech translation system VERBMOBIL. In contrast to conventional dialogue systems it mediates the dialogue while processing maximally 50% of the dialogue in depth. Special requirements like robustness and efficiency lead to a 3-layered hybrid architecture for the dialogue module, using statistics, an automaton and a planner. A dialogue memory is constructed incrementally.Comment: Postscript file, compressed and uuencoded, 15 pages, to appear in Proceedings of EACL-95, Dublin

“Advice and Consent” In the Appointments Clause: From Another Historical Perspective

This Essay, a response to Russell L. Weaver\u27s symposium contribution, Advice and Consent in Historical Perspective, first explores the Appointments Clause’s antecedents in the Age of Enlightenment and its emergence in the Constitutional Convention in 1787, showing how its sturdy separation-of-powers foundation was built. In Part II, the Essay focuses on the historical realities of the Clause’s two-branch process, especially how the operability of two political bodies naturally yields results consonant with the etiquette and political sensibilities of the day. Then, in Part III, it offers several suggestions on how to cabin the potentially untrammeled discretion of the Senate in responding to presidential nominations

Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems

This paper presents the Frames dataset (Frames is available at http://datasets.maluuba.com/Frames), a corpus of 1369 human-human dialogues with an average of 15 turns per dialogue. We developed this dataset to study the role of memory in goal-oriented dialogue systems. Based on Frames, we introduce a task called frame tracking, which extends state tracking to a setting where several states are tracked simultaneously. We propose a baseline model for this task. We show that Frames can also be used to study memory in dialogue management and information presentation through natural language generation

FEMA's Integration of Preparedness and Development of Robust Regional Offices

In October 2006, Congress enacted major legislation to reform the function and organization of the Federal Emergency Management Agency (FEMA) in response to the recognized failures in preparation for and response to Hurricane Katrina. The Post-Katrina Emergency Management Reform Act of 2006 (PKEMRA) focused national preparedness responsibilities within FEMA and directed additional resources and responsibilities to FEMA's ten regional offices. Directed by Congress, in October 2008 a National Academy Panel began an independent assessment of FEMA's integration of preparedness functions and progress in development of robust regional offices.Main FindingsOver the past three years, FEMA has taken significant steps in an effort to integrate preparedness and develop more robust regional offices. These efforts, undertaken by both the previous and current Administrations, are documented throughout this report and should be recognized and applauded. However, FEMA has yet to define specific goals and outcomes that would permit it, Congress or the public to determine when preparedness has been fully integrated into all aspects of FEMA's work and whether the development and ongoing operation of robust regional offices has been achieved. In the absence of well-defined, measurable outcome indicators, the National Academy Panel relied upon the assessments of FEMA leaders and staff, documentation provided by FEMA, and a review of secondary sources material to inform its findings and recommendations. Based upon this evidence, the Panel has concluded that, while progress has been made: (1) preparedness is not fully integrated across FEMA, (2) FEMA's regional offices do not yet have the capacity required to ensure the nation is fully prepared, (3) stakeholders are not yet full partners with FEMA in national preparedness, and (4) FEMA has ineffective internal business practices, particularly with regard to human resource management. The Panel made seven recommendations for FEMA:Establish a cross-organizational process, with participation from internal and external stakeholders, to develop a shared understanding of preparedness integrationEstablish a robust set of outcome metrics and standards for preparedness integration, as well as a system to monitor and evaluate progress on an ongoing basisWork to eliminate organizational barriers that are adversely impacting the full integration of preparedness across the agencyContinue to build regional office capacity and monitor implementation consistent with the Administrator's recent policy guidanceUndertake steps to improve the ongoing working relationship between headquarters and the regions in accord with Panel-identified principlesTake steps to improve stakeholder engagement and relationships at all levels in accord with Panel-identified principles; andStrengthen internal business practices, especially in the area of human capital planning

Harmonisation, decentralisation and local governance: Enhancing aid effectiveness

During the last decades, international development assistance was often marked by overlaps, duplication of efforts and rivalry between multitudes of donor organisations. In order to translate the principles of the Paris Declaration into practice in the field of Local Governance and Decentralisation (LGD), different donor organisations have joined forces on headquarter level and formed a working group, the Development Partners Working Group for Local Governance and Decentralisation (DPWG-LGD), which is operating since 2006. InWEnt is hosting the secretariat of the group since 2008 and assigned Wageningen International to organise two lead donor workshops. The workshop drew a cross section of delegates who comprised development partners, consultants, academicians, members of parliament and local governance practitioners. The partner countries included Rwanda, Ghana, Tanzania and Uganda whose experiences were mutually re-enforcing and beneficial

Information extraction

In this paper we present a new approach to extract relevant information by knowledge graphs from natural language text. We give a multiple level model based on knowledge graphs for describing template information, and investigate the concept of partial structural parsing. Moreover, we point out that expansion of concepts plays an important role in thinking, so we study the expansion of knowledge graphs to use context information for reasoning and merging of templates