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Deep neural networks have become a veritable alternative to classic speaker recognition and clustering methods in recent years. However, while the speech signal clearly is a time series, and despite the body of literature on the benefits of prosodic (suprasegmental) features, identifying voices has usually not been approached with sequence learning methods. Only recently has a recurrent neural network (RNN) been successfully applied to this task, while the use of convolutional neural networks (CNNs) (that are not able to capture arbitrary time dependencies, unlike RNNs) still prevails. In this paper, we show the effectiveness of RNNs for speaker recognition by improving state of the art speaker clustering performance and robustness on the classic TIMIT benchmark. We provide arguments why RNNs are superior by experimentally showing a “sweet spot” of the segment length for successfully capturing prosodic information that has been theoretically predicted in previous work.
Die Stiftung – CLUB OF HAMBURG widmet sich wissenschaftlich fundiert und praxisorientiert dem zeitgemäßen Verständnis unternehmerischen Erfolgs. Nach Überzeugung ihrer Stifter und Partner bilden wirtschaftlicher Erfolg und anständige Unternehmensführung eine untrennbare Einheit.
Anständiges Verhalten bedeutet nicht nur die legitimen Erwartungen der Gesellschaft und der eigenen Organisation zu berücksichtigen, sondern auch grundlegende ethische Werte und Prinzipien sowie daraus abgeleitete Normen, Gesetze und Regelungen zu respektieren und einzuhalten. Aus dieser Überzeugung heraus verfolgt die Stiftung das Ziel, Führungskräfte auf allen Managementebenen zur Umsetzung einer umfassend werteorientierten Unternehmensführung anzuregen und praxisorientiert zu unterstützen.
In enger Zusammenarbeit mit Unternehmen und spezialisierten Forschungseinrichtungen wurde das Entwicklungsmodell „Erfolg mit Anstand“ entwickelt. Das Modell verbindet die Inhalte einschlägiger globaler Standards mit den praktischen Erfahrungen aus der Evaluierung und Zertifizierung verantwortlicher, exzellenter Unternehmensführung. Auf diese Weise kann „ehrbares Verhalten“ von Unternehmen nicht nur bewertet und zertifiziert, sondern auch dokumentiert und extern nachvollziehbar gemacht werden. Das Entwicklungsmodell bildet die normative Basis des DEX Deutscher Ethik Index. Als Ergänzung zum rein Shareholder-Value-orientierten DAX steht der DEX Deutscher Ethik Index Unternehmen und Organisationen aller Größen, Branchen und Rechtsformen offen. Er dokumentiert den unternehmensethischen Fortschritt als Basis des wirtschaftlichen Erfolgs unter den Rahmenbedingungen des 21. Jahrhunderts nachweislich und breitenwirksam.
Today’s markets are characterized by fast and radical changes, posing an essential challenge to established companies. Startups, yet, seem to be more capable in developing radical innovations to succeed in those volatile markets. Thus, established companies started to experiment with various approaches to implement startup-like structures in their organization. Internal corporate accelerators (ICAs) are a novel form of corporate venturing, aiming to foster bottom-up innovations through intrapreneurship. However, ICAs still lack empirical investigations. This work contributes to a deeper understanding of the interface between the ICA and the core organization and the respective support activities (resource access and support services) that create an innovation-supportive work environment for the intrapreneurial team. The results of this qualitative study, comprising 12 interviews with ICA teams out of two German high-tech companies, show that the resources provided by ICAs differ from the support activities of external accelerators. Further, the study shows that some resources show both supportive as well as obstructive potential for the intrapreneurial teams within the ICA.
Further applications of the Cauchon algorithm to rank determination and bidiagonal factorization
(2018)
For a class of matrices connected with Cauchon diagrams, Cauchon matrices, and the Cauchon algorithm, a method for determining the rank, and for checking a set of consecutive row (or column) vectors for linear independence is presented. Cauchon diagrams are also linked to the elementary bidiagonal factorization of a matrix and to certain types of rank conditions associated with submatrices called descending rank conditions.
Jahresbericht 2018
(2018)
Im Sinne einer dialogischen, transdisziplinären Auseinandersetzung zwischen künstlerischer Praxis, Kultur- und Ingenieurwissenschaften geht es bei diesem Projekt um die Entwicklung einer künstlerisch-wissenschaftlichen Fallstudie mit den Zielen der konkreten Erarbeitung eines Kunstwerks unter den Bedingungen digitaler Medien - und um eine Befragung dieser Medien aus der Perspektive der
künstlerischen Praxis, der Interfacegestaltung und der Entwurfswissenschaften (Teil der UDK Berlin).
Bericht aus dem Freistellungssemester Sommer 2018
We propose a novel end-to-end neural network architecture that, once trained, directly outputs a probabilistic clustering of a batch of input examples in one pass. It estimates a distribution over the number of clusters k, and for each 1≤k≤kmax, a distribution over the individual cluster assignment for each data point. The network is trained in advance in a supervised fashion on separate data to learn grouping by any perceptual similarity criterion based on pairwise labels (same/different group). It can then be applied to different data containing different groups. We demonstrate promising performance on high-dimensional data like images (COIL-100) and speech (TIMIT). We call this “learning to cluster” and show its conceptual difference to deep metric learning, semi-supervise clustering and other related approaches while having the advantage of performing learnable clustering fully end-to-end.
Algorithms for calculating the string edit distance are used in e.g. information retrieval and document analysis systems or for evaluation of text recognizers. Text recognition based on CTC-trained LSTM networks includes a decoding step to produce a string, possibly using a language model, and evaluation using the string edit distance. The decoded string can further be used as a query for database search, e.g. in document retrieval. We propose to closely integrate dictionary search with text recognition to train both combined in a continuous fashion. This work shows that LSTM networks are capable of calculating the string edit distance while allowing for an exchangeable dictionary to separate learned algorithm from data. This could be a step towards integrating text recognition and dictionary search in one deep network.
Offline handwriting recognition systems often use LSTM networks, trained with line- or word-images. Multi-line text makes it necessary to use segmentation to explicitly obtain these images. Skewed, curved, overlapping, incorrectly written text, or noise can lead to errors during segmentation of multi-line text and reduces the overall recognition capacity of the system. Last year has seen the introduction of deep learning methods capable of segmentation-free recognition of whole paragraphs. Our method uses Conditional Random Fields to represent text and align it with the network output to calculate a loss function for training. Experiments are promising and show that the technique is capable of training a LSTM multi-line text recognition system.
In tourism, energy demands are particularly high.Tourism facilities such as hotels require large amounts ofelectric and heating resp. cooling energy. Their supply howeveris usually still based on fossil energies. This research approachanalyses the potential of promoting renewable energies in BlackForest tourism. It focuses on a combined and hence highlyefficient production of both electric and thermal energy bybiogas plants on the one hand and its provision to local tourismfacilities via short distance networks on the other. Basing onsurveys and qualitative empiricism and considering regionalresource availability as well as socio-economic aspects, it thusexamines strengths, weaknesses, opportunities and threats thatcan arise from such a cooperation.