We investigate the application of a variety of content-based image retrieval techniques to the problem of video retrieval. We generate large numbers of features for each of the key frames selected by a highly effective shot boundary detection algorithm to facilitate a query by example type search. The retrieval performance of two learning methods, boosting and k-nearest neighbours, is compared ...

In this paper, we propose a novel approach for query modeling using neural networks for posteriorgram based keyword search (KWS). We aim to help the conventional large vocabulary continuous speech recognition (LVCSR) based KWS systems, especially on out-of-vocabulary (OOV) terms by converting the task into a template matching problem, just like the query-by-example retrieval tasks. For this, we...

State of the art query by example spoken term detection (QbE-STD) systems rely on representation of speech in terms of sequences of class-conditional posterior probabilities estimated by deep neural network (DNN). The posteriors are often used for pattern matching or dynamic time warping (DTW). Exploiting posterior probabilities as speech representation propounds diverse advantages in a classif...

The vector representations of fixed dimensionality for words (in text) offered by Word2Vec have been shown to be very useful in many application scenarios, in particular due to the semantic information they carry. This paper proposes a parallel version, the Audio Word2Vec. It offers the vector representations of fixed dimensionality for variable-length audio segments. These vector representatio...

Software engineering methodologies propose that developers should capture their efforts in ensuring that programs run correctly in repeatable and automated artifacts, such as unit tests. However, when looking at developer activities on a spectrum from exploratory testing to scripted testing we find that many engineering activities include bursts of exploratory testing. In this paper we propose ...

Recognizing group activities is challenging due to the difficulties in isolating individual entities, finding the respective roles played by the individuals and representing the complex interactions among the participants. Individual actions and group activities in videos can be represented in a common framework as they share the following common feature: both are composed of a set of low-level...

We address the problem of classifying multiword expression tokens in running text. We focus our study on Verb-Noun Constructions (VNC) that vary in their idiomaticity depending on context. VNC tokens are classified as either idiomatic or literal. We present a supervised learning approach to the problem. We experiment with different features. Our approach yields the best results to date on MWE c...

The long-pending research challenge of the association rule mining task is to identify, out of the multitude of discovered rules, the ones that are interesting for the domain expert. We will demonstrate a new feature of the SEWEBAR-CMS system that allows using any of the rules as a query-by-example, and in one click, discover whether this rule is in some interesting relation to a rule already s...

Mit wachsenden technischen Fähigkeiten und gestiegenen Rechenkapazitäten dringen autonomeRoboter immerweiter in bislang undenkbareAnwendungsfelder vor. Die effiziente Programmierung des gewünschten Roboterverhaltens zählt dabei zu einem der herausforderndsten Themen in der Robotik. Verfahren, die ausschließlich auf Lernen basieren, haben den Nachteil einer langen Lerndauer. Imitation ist hier a...

We present a novel framework for intelligent search and retrieval by image region composition. Unlike traditional Query-by-Example paradigm, no starting example image is used : the user provides its mental representation of target image by means of a region photometric thesaurus. It gives an overview of the database content in the query interface. Unsupervised generation of this thesaurus is ba...