@techreport{AuerehemEbner2011, type = {Working Paper}, author = {Auer (ehem. Ebner), Veronika}, title = {Einflussgr{\"o}ßen zur mathematischen Modellierung der verkehrstr{\"a}ger{\"u}bergreifenden Tourenplanung f{\"u}r die trimodale Holztransportlogistik.}, year = {2011}, abstract = {In dieser Arbeit werden zun{\"a}chst die Facetten der Rundholztransportlogistik als Spezialgebiet der Verkehrslogistik sowie die derzeitige Tourenplanung beim Rundholztransport und damit der bestehende Handlungsbedarf von theoretischer Seite er{\"o}rtert. Mithilfe einer umfangreichen Expertenbefragung wird der praktische Handlungsbedarf zur Optimierung der gebrochenen Rundholzlogistik in Deutschland gest{\"u}tzt. Nachfolgend werden s{\"a}mtliche Einflussgr{\"o}ßen zur mathematischen Modellierung gelistet und n{\"a}her betrachtet. Abschließend finden sich eine konkrete Handlungsempfehlung sowie ein umfassender Ausblick f{\"u}r das bearbeitete Themengebiet.}, language = {de} } @incollection{Versen2011, author = {Versen, Martin}, title = {DRAM Failure Analysis and Defect Localization Techniques, Microelectronics Failure Analysis}, series = {Desk Reference Sixth Edition}, booktitle = {Desk Reference Sixth Edition}, publisher = {ASM International}, address = {Ohio}, publisher = {Technische Hochschule Rosenheim}, year = {2011}, abstract = {Comprehensive guide to the process and test methods used for electronic device failure analysis. Contains dozens of articles—contributed by industry experts—covering a wide range of topics involving the failure analysis of microelectronics. It places the most important and up-to-date information on this subject at your fingertips.  Topic coverage includes:  Failure Analysis Process Flow Failure Verification  Failure Modes and Failure Classification  Special Devices (MEMS, Optoelectronics, Passives)  Fault Localization Techniques: Package Level (NDT)  Die Level (Depackaging, Photon Emission, Microthermography, Laser-Based Methods, Particle Beam Methods)  Deprocessing \& Imaging Techniques: Deprocessing  General Imaging Techniques  Local Deprocessing \& Imaging  Circuit Edit and Design Modification  Material Analysis Techniques  Reference Information: Important Topics for Semiconductor Devices  Failure Analysis Techniques Roadmap  Failure Analysis Operations and Management  Appendices: Failure Analysis Terms, Definitions, and Acronyms  Industry Standards}, language = {en} } @inproceedings{Versen2011, author = {Versen, Martin}, title = {Worst Case Test Conditions for Defect Localization in DRAM Devices}, series = {Microelectronics Seminar of the ISTFA 2011}, booktitle = {Microelectronics Seminar of the ISTFA 2011}, year = {2011}, language = {en} } @techreport{Seidlmeier2011, author = {Seidlmeier, Heinrich}, title = {Vom Prozessmodell „automatisch" zum ausf{\"u}hrbaren Workflow mit der ARIS Process Governance}, year = {2011}, language = {de} } @inproceedings{Schanda2011, author = {Schanda, Ulrich}, title = {Resonant system for the absorption of low frequency impact noise and for the damping of low frequency vibrations}, series = {European Acoustics Association (EAA) (ed.), Forum Acusticum}, booktitle = {European Acoustics Association (EAA) (ed.), Forum Acusticum}, year = {2011}, language = {de} } @inproceedings{SchroederSchanda2011, author = {Schr{\"o}der, E. and Schanda, Ulrich}, title = {Untersuchungen zur Sprachverst{\"a}ndlichkeit als raumakustischer Parameter von Mehrpersonenb{\"u}ros}, series = {Deutsche Gesellschaft f{\"u}r Akustik e.V. DAGA}, booktitle = {Deutsche Gesellschaft f{\"u}r Akustik e.V. DAGA}, year = {2011}, language = {de} } @inproceedings{RiedhammerGroppNoeth2011, author = {Riedhammer, Korbinian and Gropp, Martin and N{\"o}th, Elmar}, title = {A Novel Lecture Browser Using Key Phrases and Stream Graphs}, series = {Lehrstuhl f{\"u}r Mustererkennung, Universit{\"a}t Erlangen-N{\"u}rnberg}, booktitle = {Lehrstuhl f{\"u}r Mustererkennung, Universit{\"a}t Erlangen-N{\"u}rnberg}, year = {2011}, abstract = {We present a novel lecture browser that utilizes ranked key phrases displayed on a stream graph to overcome the shortcomings of traditional extractive (query-based) summaries. The system extracts key phrases from the ASR transcripts, performs an unsupervised ranking, and displays an initial number of phrases on the stream graph. This graph gives an intuition of when which key phrase is spoken, and how dominant it is throughout the lecture. The user can select the phrases to be displayed and furthermore adjust the ranking of the all phrases. All user interactions are logged to a server to improve the ranking algorithms and provide user specific rankings.}, language = {en} } @inproceedings{GroppNoethRiedhammer2011, author = {Gropp, Martin and N{\"o}th, Elmar and Riedhammer, Korbinian}, title = {A Novel Lecture Browsing System Using Ranked Key Phrases and StreamGraphs}, series = {14th International Conference on Text, Speech and Dialogue (TSD), September 2011, Pilsen, Czech Republic.}, booktitle = {14th International Conference on Text, Speech and Dialogue (TSD), September 2011, Pilsen, Czech Republic.}, pages = {17 -- 24}, year = {2011}, abstract = {A growing number of universities offer recordings of lectures, seminars and talks in an online e-learning portal. However, the user is often not interested in the entire recording, but is looking for parts covering a certain topic. Usually, the user has to either watch the whole video or "zap" through the lecture and risk missing important details. We present an integrated web-based platform to help users find relevant sections within recorded lecture videos by providing them with a ranked list of key phrases. For a user-defined subset of these, a StreamGraph visualizes when important key phrases occur and how prominent they are at the given time. To come up with the best key phrase rankings, we evaluate three different key phrase ranking methods using lectures of different topics by comparing automatic with human rankings, and show that human and automatic rankings yield similar scores using Normalized Discounted Cumulative Gain (NDCG).}, language = {en} } @inproceedings{SteidlRiedhammerBockletetal.2011, author = {Steidl, Stefan and Riedhammer, Korbinian and Bocklet, Tobias and H{\"o}nig, Florian and N{\"o}th, Elmar}, title = {Java Visual Speech Components for Rapid Application Development of GUI based Speech Processing Applications}, series = {INTERSPEECH 2011, 12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 2011.}, booktitle = {INTERSPEECH 2011, 12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 2011.}, pages = {3257 -- 3260}, year = {2011}, abstract = {In this paper, we describe a new Java framework for an easy and efficient way of developing new GUI based speech processing applications. Standard components are provided to display the speech signal, the power plot, and the spectrogram. Furthermore, a component to create a new transcription and to display and manipulate an existing transcription is provided, as well as a component to display and manually correct external pitch values. These Swing components can be easily embedded into own Java programs. They can be synchronized to display the same region of the speech file. The object-oriented design provides base classes for rapid development of own components.}, language = {en} } @inproceedings{BockletRiedhammerNoeth2011, author = {Bocklet, Tobias and Riedhammer, Korbinian and N{\"o}th, Elmar}, title = {Drink and Speak: On the automatic classification of alcohol intoxination by acoustic, prosodic and text-based features}, series = {INTERSPEECH 2011, 12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 2011.}, booktitle = {INTERSPEECH 2011, 12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 2011.}, pages = {3213 -- 3216}, year = {2011}, abstract = {This paper focuses on the automatic detection of a person's blood level alcohol based on automatic speech processing approaches. We compare 5 different feature types with different ways of modeling. Experiments are based on the ALC corpus of IS2011 Speaker State Challenge. The classification task is restricted to the detection of a blood alcohol level above 0.5 per mille. Three feature sets are based on spectral observations: MFCCs, PLPs, TRAPS. These are modeled by GMMs. Classification is either done by a Gaussian classifier or by SVMs. In the later case classification is based on GMM-based supervectors, i.e. concatenation of GMM mean vectors. A prosodic system extracts a 292-dimensional feature vector based on a voiced-unvoiced decision. A transcription-based system makes use of text transcriptions related to phoneme durations and textual structure. We compare the stand-alone performances of these systems and combine them on score level by logistic regression. The best stand-alone performance is the transcriptionbased system which outperforms the baseline by 4.8\% on the development set. A Combination on score level gave a huge boost when the spectral-based systems were added (73.6\%). This is a relative improvement of 12.7\% to the baseline. On the test-set we achieved an UA of 68.6\% which is a significant improvement of 4.1\% to the baseline system.}, language = {en} }