TY - BOOK A1 - Riedhammer, Korbinian T1 - Interactive Approaches to Video Lecture Assessment N2 - Folks that have been here last winter prior to ASRU might be familiar with the title of that talk. But don't be misled, I'll have something new for you. In this talk, I will give an overview over the FAU Lecture Browser which I developed in the context of my thesis. I will start out with the description of a novel data set: The LME Lectures are a corpus of two series of graduate level computer science lectures with 18 recordings each. The courses cover topics in medical image processing and pattern analysis/machine learning. The roughly 40 hours of speech were manually transcribed, and one particular lecture was annotated with key phrases by five human raters. Using this data set, I trained three different speech recognizers using regular continuous, multi-codebook semi-continuous and subspace Gaussian mixture models, that show an error rate of about 10% WER. I will then briefly describe the key phrase extraction and automatic ranking, which was then compared against five raters on one lecture recording. Finally, I will talk about a little usability study where 10 students were asked to perform a certain task-- with and without the proposed lecture browser. Although the number of contestants is limited, the numbers are interesting: the users that had the interface could complete the tasks about 30% faster than the control group, while maintaining about the same accuracy. KW - Speech Recognition Y1 - 2012 PB - Logos Verlag Berlin GmbH CY - Berlin ER - TY - BOOK A1 - Riedhammer, Korbinian T1 - An Automatic Intelligibility Test Based on the Post-Laryngectomy Telephone Test KW - Speech Recognition Y1 - 2008 PB - Mueller Verlag CY - Nürnberg ER - TY - JOUR A1 - Haderlein, Tino A1 - Riedhammer, Korbinian A1 - Nöth, Elmar A1 - Toy, Hikmet A1 - Schuster, Maria A1 - Eysholdt, Ulrich A1 - Hornegger, Joachim A1 - Rosanowski, Frank T1 - Application of Automatic Speech Recognition to Quantitative Assessment of Tracheoesophageal Speech in Different Signal Quality JF - Folia Phoniatrica Et Logopaedica N2 - Tracheoesophageal voice is state-of-the-art in voice rehabilitation after laryngectomy. Intelligibility on a telephone is an important evaluation criterion as it is a crucial part of social life. An objective measure of intelligibility when talking on a telephone is desirable in the field of postlaryngectomy speech therapy and its evaluation. Based upon successful earlier studies with broadband speech, an automatic speech recognition (ASR) system was applied to 41 recordings of postlaryngectomy patients. Recordings were available in different signal qualities; quality was the crucial criterion for this study. Compared to the intelligibility rating of 5 human experts, the ASR system had a correlation coefficient of r = -0.87 and Krippendorff's alpha of 0.65 when broadband speech was processed. The rater group alone achieved alpha = 0.66. With the test recordings in telephone quality, the system reached r = -0.79 and alpha = 0.67. For medical purposes, a comprehensive diagnostic approach to (substitute) voice has to cover both subjective and objective tests. An automatic recognition system such as the one proposed in this study can be used for objective intelligibility rating with results comparable to those of human experts. This holds for broadband speech as well as for automatic evaluation via telephone. KW - Speech Recognition Software Y1 - 2008 VL - 2008 IS - 61(1) SP - 12 EP - 17 ER - TY - JOUR A1 - Bocklet, Tobias A1 - Riedhammer, Korbinian A1 - Nöth, Elmar A1 - Eysholdt, Ulrich A1 - Haderlein, Tino T1 - Automatic Intelligibility Assessment of Speakers After Laryngeal Cancer by Means of Acoustic Modeling JF - Journal of Voice N2 - One aspect of voice and speech evaluation after laryngeal cancer is acoustic analysis. Perceptual evaluation by expert raters is a standard in the clinical environment for global criteria such as overall quality or intelligibility. So far, automatic approaches evaluate acoustic properties of pathologic voices based on voiced/unvoiced distinction and fundamental frequency analysis of sustained vowels. Because of the high amount of noisy components and the increasing aperiodicity of highly pathologic voices, a fully automatic analysis of fundamental frequency is difficult. We introduce a purely data-driven system for the acoustic analysis of pathologic voices based on recordings of a standard text. KW - Speech Recognition KW - Lung cancer technologies Y1 - 2012 IS - 26(3) SP - 390 EP - 397 ER - TY - JOUR A1 - Riedhammer, Korbinian A1 - Favre, Benoit A1 - Hakkani-Tür, Dilek T1 - Long story short - Global unsupervised models for keyphrase based meeting summarization JF - SPEECH COMMUNICATION KW - Speech Recognition KW - Meeting Summarization Y1 - 2010 VL - 2010 IS - 52(10) SP - 801 EP - 815 ER - TY - JOUR A1 - Tur, Gokhan A1 - Stolcke, Andreas A1 - Voss, Lynn A1 - Peters, Stanley A1 - Hakkani-Tür, Dilek A1 - Dowding, John A1 - Favre, Benoit A1 - Fernandez, Raquel A1 - Frampton, Matthew A1 - Frandsen, Michael A1 - Frederickson, Clint A1 - Graciarena, Martin A1 - Kintzing, Donald A1 - Leveque, Kyle A1 - Mason, Shane A1 - Niekrasz, John A1 - Purver, Matthew A1 - Riedhammer, Korbinian A1 - Shriberg, Elizabeth A1 - Tien, Jing A1 - Vergyri, Dimitra A1 - Yang, Fan T1 - The CALO Meeting Assistant System JF - IEEE Transactions on Audio, Speech and Language Processing N2 - The CALO Meeting Assistant (MA) provides for distributed meeting capture, annotation, automatic transcription and semantic analysis of multiparty meetings, and is part of the larger CALO personal assistant system. This paper presents the CALO-MA architecture and its speech recognition and understanding components, which include real-time and offline speech transcription, dialog act segmentation and tagging, topic identification and segmentation, question-answer pair identification, action item recognition, decision extraction, and summarization. KW - Multiparty meetings processing KW - speech recognition KW - spoken language understanding Y1 - 2010 VL - 2010 IS - 18(6) SP - 1601 EP - 1611 ER - TY - JOUR A1 - Haderlein, Tino A1 - Riedhammer, Korbinian A1 - Maier, Andreas A1 - Nöth, Elmar A1 - Eysholdt, Ulrich A1 - Rosanowski, Frank T1 - Automatisierung des Postlaryngektomie-Telefontests JF - HNO N2 - In dieser Studie wird ein objektives Verfahren für die Verständlichkeitsmessung mit dem Postlaryngektomie-Telefontest (PLTT) mittels automatischer Spracherkennungstechnik beschrieben. 31 Sprecher mit tracheoösophagealer Ersatzstimme (25 Männer und 6 Frauen; 63,4±8,7 Jahre) wurden zunächst von 11 naiven Hörern bewertet. Der vom Spracherkennungssystem ermittelte Verständlichkeitsgrad wird als Prozentsatz korrekt verstandener Wörter einer Wortkette, der Wortakkuratheit bzw. -korrektheit, angegeben und mit den subjektiv ermittelten PLTT-Werten verglichen. Die durchschnittliche PLTT-Gesamtverständlichkeit der 11 naiven Hörer liegt bei 47%, die automatisch ermittelte Wortakkuratheit und Wortkorrektheit liegen deutlich niedriger (etwa 0% bzw. etwa 15%). Die Korrelation zwischen menschlicher und maschineller Bewertung liegt jedoch z. T. über 0,9. Für den Gesamtverständlichkeitswert des PLTT kann mit Hilfe der automatischen Spracherkennung objektiv und effizient ein äquivalentes Maß berechnet werden. KW - Spracherkennungssoftware KW - Automatische Mustererkennung KW - Sprechverständlichkeit KW - Auswertungsmethoden KW - Korrelation von Daten Y1 - 2009 VL - 2009 IS - 57 SP - 51 EP - 56 PB - Springer-Verlag ER - TY - CHAP A1 - Bayerl, Sebastian P. A1 - Wenninger, Marc A1 - Schmidt, Jochen A1 - Wolff von Gudenberg, Alexander A1 - Riedhammer, Korbinian T1 - STAN: A stuttering therapy analysis helper T2 - 2021 IEEE Spoken Language Technology Workshop (SLT) N2 - Stuttering is a complex speech disorder identified by repetitions, prolongations of sounds, syllables or words and blockswhile speaking. Specific stuttering behaviour differs strongly,thus needing personalized therapy. Therapy sessions requirea high level of concentration by the therapist. We introduce STAN, a system to aid speech therapists in stuttering therapysessions. Such an automated feedback system can lower the cognitive load on the therapist and thereby enable a more consistent therapy as well as allowing analysis of stuttering over the span of multiple therapy sessions. KW - Machine Learning Y1 - 2021 ER -