TY - CHAP A1 - Spiegl, Werner A1 - Riedhammer, Korbinian A1 - Steidl, Stefan A1 - Nöth, Elmar T1 - FAU IISAH Corpus – A German Speech Database Consisting of Human-Machine and Human-Human Interaction Acquired by Close-Talking and Far-Distance Microphones T2 - 7th Conference on International Language Resources and Evaluation (LREC 2010), European Language Resources Association (ELRA), Valletta, Malta, May 2010. KW - Speech Recognition Y1 - 2018 SP - 2420 EP - 2423 ER - TY - CHAP A1 - Bocklet, Tobias A1 - Maier, Andreas A1 - Riedhammer, Korbinian A1 - Nöth, Elmar T1 - Towards a Language-independent Intelligibility Assessment of Children with Cleft Lip and Palate T2 - WOCCI '09 Proceedings of the 2nd Workshop on Child, Computer and Interaction (WOCCI 2009), Cambridge, Massachusetts, November 2009, Article No. 6. N2 - We describe a novel evaluation system for the intelligibility assessment of children with CLP on standardized tests. The system is solely based on standard cepstral features in form of MFCCs. No other information like word alignments is used. So the system can be easily adapted to other languages. For each child one GMM is created by adaptation of a UBM to the speaker-specific MFCCs. The components of this GMM are concatenated in order to create a so-called GMM supervector. These GMM supervectors are then used as meta features for an SVR. We evaluated our language-independent system on two different datasets of children suffering from CLP. One dataset contains recordings of 35 German children, where the children named different pictograms. The other dataset contains recordings of 14 Italian speaking children, who repeated standardized sentences. On both datasets we achieved high correlations: up to 0.81 for the German dataset and 0.83 for the Italian dataset. KW - Speech Recognition Y1 - 2009 SP - 2015 EP - 2018 ER - TY - CHAP A1 - Faria, Arlo A1 - Riedhammer, Korbinian A1 - Janin, Adam A1 - Bauer, A. T1 - REMEETING: Searchable Conversations T2 - INTERSPEECH 2016, Annual Conference of the International Speech Communication Association (ISCA), IEEE Workshop on Spoken Language Technologies (SLT), San Francisco, USA, September 2016. KW - Speech Recognition Y1 - 2016 ER - TY - CHAP A1 - Faria, Arlo A1 - Riedhammer, Korbinian T1 - REMEETING — Get More Out Of Meetings T2 - INTERSPEECH 2015, 16th Annual Conference of the International Speech Communication Association, Dresden, Germany, September 2015. N2 - Remeeting is a tool that helps you get more out of in-person meetings. Calendar integration and a special email address allow users to email agenda items prior to a certain meeting. A discrete notification at the time of the meeting reminds the user to start the recording. During the meeting, the user focuses on the conversation, or can add notes and photos if desired. After the meeting, every participant gets notified by an automated email that lists the participants along with automatically extracted keywords, notes and photos. This stimulates collaboration, and keeps follow-up contributions at a central place: Just reply to add further notes to the meeting. The resulting meeting “document” can be shared with others and reviewed using a web app that acts as a visual index to the meeting. This makes Remeeting the perfect tool for regular group meetings, standups and interviews, where people typically track progress and follow up on. Remeeting is leveraging, promoting and contributing to open source projects including kaldi and docker. KW - Speech Recognition KW - speaker identification KW - automatic summarization KW - productivity Y1 - 2015 ER - TY - CHAP A1 - Faria, Arlo A1 - Riedhammer, Korbinian T1 - REMEETING — Get More Out of Meetings T2 - INTERSPEECH 2014, 15th Annual Conference of the International Speech Communication Association, IEEE Workshop on Spoken Language Technologies (SLT), Singapore, September 2014. KW - Speech Recognition KW - speaker identification KW - automatic summarization KW - productivity Y1 - 2014 ER - TY - CHAP A1 - Garg, Nikhil A1 - Favre, Benoit A1 - Riedhammer, Korbinian A1 - Hakkani-Tür, Dilek T1 - A Graph Based Method for Meeting Summarization T2 - INTERSPEECH 2009, 10th Annual Conference of the International Speech Communication Association, Brighton, United Kingdom, September 2009. N2 - This paper presents an unsupervised, graph based approach for extractive summarization of meetings. Graph based methods such as TextRank have been used for sentence extraction from news articles. These methods model text as a graph with sentences as nodes and edges based on word overlap. A sentence node is then ranked according to its similarity with other nodes. The spontaneous speech in meetings leads to incomplete, informed sentences with high redundancy and calls for additional measures to extract relevant sentences. We propose an extension of the TextRank algorithm that clusters the meeting utterances and uses these clusters to construct the graph. We evaluate this method on the AM I meeting corpus and show a significant improvement over TextRank and other baseline methods. KW - Summarization KW - Page Rank Y1 - 2009 SP - 1499 EP - 1502 ER - TY - CHAP A1 - Gillick, Dan A1 - Riedhammer, Korbinian A1 - Favre, Benoit A1 - Hakkani-Tür, Dilek T1 - A Global Optimization Framework for Meeting Summarization T2 - 2009 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Taipei, Taiwan, April 2009. N2 - We introduce a model for extractive meeting summarization based on the hypothesis that utterances convey bits of information, or concepts. Using keyphrases as concepts weighted by frequency, and an integer linear program to determine the best set of utterances, that is, covering as many concepts as possible while satisfying a length constraint, we achieve ROUGE scores at least as good as a ROUGE-based oracle derived from human summaries. This brings us to a critical discussion of ROUGE and the future of extractive meeting summarization. KW - meeting summarization KW - integer linear programming KW - summarization evaluation Y1 - 2009 SP - 4769 EP - 4772 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Favre, Benoit A1 - Hakkani-Tür, Dilek T1 - A Keyphrase Based Approach to Interactive Meeting Summarization T2 - 2008 IEEE Workshop on Spoken Language Technologies (SLT), Goa, India, December 2008. N2 - Rooted in multi-document summarization, maximum marginal relevance (MMR) is a widely used algorithm for meeting summarization (MS). A major problem in extractive MS using MMR is finding a proper query: the centroid based query which is commonly used in the absence of a manually specified query, can not significantly outperform a simple baseline system. We introduce a simple yet robust algorithm to automatically extract keyphrases (KP) from a meeting which can then be used as a query in the MMR algorithm. We show that the KP based system significantly outperforms both baseline and centroid based systems. As human refined KPs show even better summarization performance, we outline how to integrate the KP approach into a graphical user interface allowing interactive summarization to match the user's needs in terms of summary length and topic focus. KW - meeting summarization KW - keyword generation KW - user interaction Y1 - 2008 SP - 153 EP - 156 ER - TY - CHAP A1 - Tur, Gokhan A1 - Stolcke, Andreas A1 - Voss, Lynn A1 - Dowding, John A1 - Favre, Benoit A1 - Fernandez, Raquel A1 - Frampton, Matthew A1 - Frandsen, Michael A1 - Frederickson, Clive A1 - Graciarena, Martin A1 - Hakkani-Tür, Dilek A1 - Kintzing, Donald A1 - Leveque, Kyle A1 - Mason, Shane A1 - Niekrasz, John A1 - Peters, Stanley A1 - Purver, Matthew A1 - Riedhammer, Korbinian A1 - Shriberg, Elizabeth A1 - Tien, Jing A1 - Vergyri, Dimitra A1 - Yang, Fan T1 - The CALO Meeting Speech Recognition and Understanding System T2 - 2008 IEEE Workshop on Spoken Language Technologies (SLT), Goa, India, December 2008. N2 - The CALO meeting assistant 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 summarizes the CALO-MA architecture and its speech recognition and understanding components, which include real-time and offline speech transcription, dialog act segmentation and tagging, question-answer pair identification, action item recognition, decision extraction, and summarization. KW - Speech Recognition KW - multiparty meetings processing KW - spoken language understanding Y1 - 2008 SP - 69 EP - 72 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Gillick, Dan A1 - Favre, Benoit A1 - Hakkani-Tür, Dilek T1 - Packing the Meeting Summarization Knapsack T2 - INTERSPEECH 2008, 9th Annual Conference of the International Speech Communication Association (ISCA), Brisbane, Australia, September 2008. N2 - Despite considerable work in automatic meeting summarization over the last few years, comparing results remains difficult due to varied task conditions and evaluations. To address this issue, we present a method for determining the best possible extractive summary given an evaluation metric like ROUGE. Our oracle system is based on a knapsack-packing framework, and though NP-Hard, can be solved nearly optimally by a genetic algorithm. To frame new research results in a meaningful context, we suggest presenting our oracle results alongside two simple baselines. We show oracle and baseline results for a variety of evaluation scenarios that have recently appeared in this field. KW - summarization KW - meetings KW - evaluation Y1 - 2008 SP - 2434 EP - 2437 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Stemmer, Georg A1 - Haderlein, Tino A1 - Schuster, Mario A1 - Rosanowski, Frank A1 - Nöth, Elmar A1 - Maier, Andreas T1 - Towards Robust Automatic Evaluation of Pathologic Telephone Speech T2 - 2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU), Kyoto, Japan, December 2007. N2 - For many aspects of speech therapy an objective evaluation of the intelligibility of a patient's speech is needed. We investigate the evaluation of the intelligibility of speech by means of automatic speech recognition. Previous studies have shown that measures like word accuracy are consistent with human experts' ratings. To ease the patient's burden, it is highly desirable to conduct the assessment via phone. However, the telephone channel influences the quality of the speech signal which negatively affects the results. To reduce inaccuracies, we propose a combination of two speech recognizers. Experiments on two sets of pathological speech show that the combination results in consistent improvements in the correlation between the automatic evaluation and the ratings by human experts. Furthermore, the approach leads to reductions of 10% and 25% of the maximum error of the intelligibility measure. KW - Biomedical acoustics KW - Speech intelligibility KW - Speech processing KW - Acoustic applications Y1 - 2007 SP - 717 EP - 722 ER -