TY - CHAP A1 - Riedhammer, Korbinian A1 - Ring, Martin A1 - Nöth, Elmar A1 - Kolb, Daniel T1 - A Software Kit for Automatic Voice Descrambling T2 - 2012 IEEE International Conference on Communications (ICC); IEEE International Workshop on Security and Forensics in Communication Systems (SFCS). N2 - Voice scrambling is widely used to add privacy to the radio communication of various authorities - but is also used by criminals to evade prosecution. In this article, we consider various analog voice scrambling techniques such as fixed frequency inversion, splitband inversion and rolling code scramblers. We explain how to break them using automatically extracted measures and scoring algorithms, and evaluate the proposed system using simulated data. While the simple inversion can be easily broken, the more advanced techniques require additional work prior to unsupervised automatization; the presented user interface allows the user to refine the automatic results to obtain a high quality solution. KW - Speech Recognition Y1 - 2012 SP - 8349 EP - 8353 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Bocklet, Tobias A1 - Goshal, Arnab A1 - Povey, Daniel T1 - Revisiting Semi-Continuous Hidden Markov Models T2 - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, March 2012. N2 - In the past decade, semi-continuous hidden Markov models (SCHMMs) have not attracted much attention in the speech recognition community. Growing amounts of training data and increasing sophistication of model estimation led to the impression that continuous HMMs are the best choice of acoustic model. However, recent work on recognition of under-resourced languages faces the same old problem of estimating a large number of parameters from limited amounts of transcribed speech. This has led to a renewed interest in methods of reducing the number of parameters while maintaining or extending the modeling capabilities of continuous models. In this work, we compare classic and multiple-codebook semi-continuous models using diagonal and full covariance matrices with continuous HMMs and subspace Gaussian mixture models. Experiments on the RM and WSJ corpora show that while a classical semicontinuous system does not perform as well as a continuous one, multiple-codebook semi-continuous systems can perform better, particular when using full-covariance Gaussians. KW - automatic speech recognition KW - acoustic modeling Y1 - 2012 SP - 4721 EP - 4724 PB - IEEE ER - TY - CHAP A1 - Povey, Daniel A1 - Hannemann, Mirko A1 - Boulianne, Gilles A1 - Burget, Lukáš A1 - Ghoshal, Arnab A1 - Janda, Miloš A1 - Karafiát, Martin A1 - Kombrink, Stefan A1 - Motlíček, Petr A1 - Qian, Yanmin A1 - Riedhammer, Korbinian A1 - Veselý, Karel A1 - Thang Vu, Ngoc T1 - Generating Exact Lattices in the WFST Framework T2 - 2012 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Kyoto, Japan, May 2012. N2 - We describe a lattice generation method that is exact, i.e. it satisfies all the natural properties we would want from a lattice of alternative transcriptions of an utterance. This method does not introduce substantial overhead above one-best decoding. Our method is most directly applicable when using WFST decoders where the WFST is “fully expanded”, i.e. where the arcs correspond to HMM transitions. It outputs lattices that include HMM-state-level alignments as well as word labels. The general idea is to create a state-level lattice during decoding, and to do a special form of determinization that retains only the best-scoring path for each word sequence. This special determinization algorithm is a solution to the following problem: Given a WFST A, compute a WFST B that, for each input-symbol-sequence of A, contains just the lowest-cost path through A. KW - Speech Recognition KW - Lattice Generation Y1 - 2012 SP - 4213 EP - 4216 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Gropp, Martin A1 - Nöth, Elmar T1 - A Novel Lecture Browser Using Key Phrases and Stream Graphs T2 - Lehrstuhl für Mustererkennung, Universität Erlangen-Nürnberg N2 - 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. KW - Speech Recognition Y1 - 2011 ER - TY - CHAP A1 - Gropp, Martin A1 - Nöth, Elmar A1 - Riedhammer, Korbinian T1 - A Novel Lecture Browsing System Using Ranked Key Phrases and StreamGraphs T2 - 14th International Conference on Text, Speech and Dialogue (TSD), September 2011, Pilsen, Czech Republic. N2 - 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). KW - key phrases KW - ranking KW - visualization KW - browsing KW - E-Learning Y1 - 2011 SP - 17 EP - 24 ER - TY - CHAP A1 - Steidl, Stefan A1 - Riedhammer, Korbinian A1 - Bocklet, Tobias A1 - Hönig, Florian A1 - Nöth, Elmar T1 - Java Visual Speech Components for Rapid Application Development of GUI based Speech Processing Applications T2 - INTERSPEECH 2011, 12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 2011. N2 - In this paper, we describe a new Java framework for an easy and efficient way of developing new GUI based speech processing applications. Standard components are provided to display the speech signal, the power plot, and the spectrogram. Furthermore, a component to create a new transcription and to display and manipulate an existing transcription is provided, as well as a component to display and manually correct external pitch values. These Swing components can be easily embedded into own Java programs. They can be synchronized to display the same region of the speech file. The object-oriented design provides base classes for rapid development of own components. KW - Speech Processing Applications KW - Java KW - Graphical User Interfaces (GUI) KW - Rapid Application Development (RAD) Y1 - 2011 SP - 3257 EP - 3260 ER - TY - CHAP A1 - Bocklet, Tobias A1 - Riedhammer, Korbinian A1 - Nöth, Elmar T1 - Drink and Speak: On the automatic classification of alcohol intoxination by acoustic, prosodic and text-based features T2 - INTERSPEECH 2011, 12th Annual Conference of the International Speech Communication Association, Florence, Italy, August 2011. N2 - This paper focuses on the automatic detection of a person's blood level alcohol based on automatic speech processing approaches. We compare 5 different feature types with different ways of modeling. Experiments are based on the ALC corpus of IS2011 Speaker State Challenge. The classification task is restricted to the detection of a blood alcohol level above 0.5‰. Three feature sets are based on spectral observations: MFCCs, PLPs, TRAPS. These are modeled by GMMs. Classification is either done by a Gaussian classifier or by SVMs. In the later case classification is based on GMM-based supervectors, i.e. concatenation of GMM mean vectors. A prosodic system extracts a 292-dimensional feature vector based on a voiced-unvoiced decision. A transcription-based system makes use of text transcriptions related to phoneme durations and textual structure. We compare the stand-alone performances of these systems and combine them on score level by logistic regression. The best stand-alone performance is the transcriptionbased system which outperforms the baseline by 4.8% on the development set. A Combination on score level gave a huge boost when the spectral-based systems were added (73.6%). This is a relative improvement of 12.7% to the baseline. On the test-set we achieved an UA of 68.6% which is a significant improvement of 4.1% to the baseline system. KW - GMM KW - alcohol intoxication KW - system fusion Y1 - 2011 SP - 3213 EP - 3216 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Bocklet, Tobias A1 - Nöth, Elmar T1 - Compensation of Extrinsic Variability in Speaker Verification Systems on Simulated Skype and HF Channel Data T2 - 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Prague, Czech Republic, May 2011. N2 - In this work we focus on speaker verification on channels of varying quality, namely Skype and high frequency (HF) radio. In our setup, we assume to have telephone recordings of speakers for training, but recordings of different channels for testing with varying (lower) signal quality. Starting from a Gaussian mixture / support vector machine (GMM/SVM) baseline, we evaluate multi-condition training (MCT), an ideal channel classification approach (ICC), and nuisance attribute projection (NAP) to compensate for the loss of information due to the transmission. In an evaluation on Switchboard-2 data using Skype and HF channel simulators, we show that, for good signal quality, NAP improves the baseline system performance from 5% EER to 3.33% EER (for both Skype and HF). For strongly distorted data, MCT or, if adequate, ICC turn out to be the method of choice. KW - speaker verification KW - channel compensation Y1 - 2011 SP - 4840 EP - 4843 ER - TY - CHAP A1 - Kiesmüller, Ulrich A1 - Sossalla, Sebastian A1 - Brinda, Torsten A1 - Riedhammer, Korbinian T1 - Online Identification of Learner Problem Solving Strategies Using Pattern Recognition Methods T2 - Proceedings of the 15th Annual Conference on Innovation and Technology in Computer Science Education (ITiCSE 2010), Bilkent, Ankara, Turkey, June 2010. N2 - Learning and programming environments used in computer science education give feedback to the users by system messages. These are triggered by programming errors and give only "technical" hints without regard to the learners' problem solving process. To adapt the messages not only to the factual but also to the procedural knowledge of the learners, their problem solving strategies have to be identified automatically and in process. This article describes a way to achieve this with the help of pattern recognition methods. Using data from a study with 65 learners aged 12 to 13 using a learning environment for programming, a classification system based on hidden Markov models is trained and integrated in the very same environment. We discuss findings in that data and the performance of the automatic online identification, and present first results using the developed software in class. KW - Pattern Recognition KW - Computer Science Education KW - Secondary Education KW - Problem Solving Strategies KW - Algorithms KW - Tool-Based Analysis Y1 - 2010 SP - 274 EP - 278 ER - TY - CHAP A1 - Zäh, Uwe A1 - Riedhammer, Korbinian A1 - Bocklet, Tobias A1 - Nöth, Elmar T1 - Clap Your Hands! Calibrating Spectral Subtraction for Dereverberation T2 - 2010 IEEE International Conference on Acoustics, Speech and Signal Processing(ICASSP), Dallas, TX, USA, March 2010. N2 - Reverberation effects as observed by room microphones severely degrade the performance of automatic speech recognition systems. We investigate the use of dereverberation by spectral subtraction as proposed by Lebart and Boucher and introduce a simple approach to estimate the required decay parameter by clapping hands. Experiments on small vocabulary continuous speech recognition task on read speech show that using the calibrated dereverberation improves WER from 73.2 to 54.7 for the best microphone. In combination with system adaptation, the WER could be reduced to 28.2, which is only a 16% relative loss of performance comparison to using a headset instead of a room microphone. KW - Speech Recognition KW - robustness Y1 - 2010 SP - 4226 EP - 4229 ER - 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 -