@inproceedings{RiedhammerGroppBockletetal.2013, author = {Riedhammer, Korbinian and Gropp, Martin and Bocklet, Tobias and H{\"o}nig, Florian and N{\"o}th, Elmar and Steidl, Stefan}, title = {LMELectures: A Multimedia Corpus of Academic Spoken English}, series = {First Workshop on Speech, Language and Audio in Multimedia (SLAM 2013), Marseille, France, August 2013, ISCA Archive.}, booktitle = {First Workshop on Speech, Language and Audio in Multimedia (SLAM 2013), Marseille, France, August 2013, ISCA Archive.}, pages = {102 -- 107}, year = {2013}, abstract = {This paper describes the acquisition, transcription and annotation of a multi-media corpus of academic spoken English, the LMELectures. It consists of two lecture se-ries that were read in the summer term 2009 at the com-puter science department of the University of Erlangen-Nuremberg, covering topics in pattern analysis, machine learning and interventional medical image processing. In total, about 40 hours of high-definition audio and video of a single speaker was acquired in a constant recording en-vironment. In addition to the recordings, the presentation slides are available in machine readable (PDF) format. The manual annotations include a suggested segmenta-tion into speech turns and a complete manual transcrip-tion that was done using BLITZSCRIBE2, a new tool for the rapid transcription. For one lecture series, the lecturer assigned key words to each recordings; one recording of that series was further annotated with a list of ranked key phrases by five human annotators each. The corpus is available for non-commercial purpose upon request.}, language = {en} } @inproceedings{RiedhammerGroppNoeth2012, author = {Riedhammer, Korbinian and Gropp, Martin and N{\"o}th, Elmar}, title = {The FAU Video Lecture Browser System}, series = {2012 IEEE Spoken Language Technology Workshop (SLT), Miami, FL, USA, December 2012.}, booktitle = {2012 IEEE Spoken Language Technology Workshop (SLT), Miami, FL, USA, December 2012.}, publisher = {IEEE}, pages = {392 -- 397}, year = {2012}, abstract = {A growing number of universities and other educational institutions provide recordings of lectures and seminars as an additional resource to the students. In contrast to educational films that are scripted, directed and often shot by film professionals, these plain recordings are typically not post-processed in an editorial sense. Thus, the videos often contain longer periods of inactivity or silence, unnecessary repetitions, or corrections of prior mistakes. This paper describes the FAU Video Lecture Browser system, a web-based platform for the interactive assessment of video lectures, that helps to close the gap between a plain recording and a useful e-learning resource by displaying automatically extracted and ranked key phrases on an augmented time line based on stream graphs. In a pilot study, users of the interface were able to complete a topic localization task about 29 \% faster than users provided with the video only while achieving about the same accuracy. The user interactions can be logged on the server to collect data to evaluate the quality of the phrases and rankings, and to train systems that produce customized phrase rankings.}, language = {en} } @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} }