TY - CHAP A1 - Riedhammer, Korbinian A1 - Bocklet, Tobias A1 - Orozco-Arroyave, Juan Rafael A1 - Nöth, Elmar T1 - Semi-Automatic Calibration for Dereverberation by Spectral Subtraction for Continuous Speech Recognition T2 - ITG Symposium on Speech Communication 2014, Erlangen. N2 - In this article, we describe a semi-automatic calibration algorithm for dereverberation by spectral subtraction. We verify the method by a comparison to a manual calibration derived from measured room impulse responses (RIR). We conduct extensive experiments to understand the effect of all involved parameters and to verify values suggested in the literature. The experiments are performed on a text read by 31 speakers and recorded by a headset and three far-field microphones. Results are measured in terms of automatic speech recognition (ASR) performance using a 1-gram model to emphasize acoustic recognition performance. To accommodate for the acoustic change by dereverberation we apply supervised MAP adaptation to the hidden Markov model output probabilities. The combination of dereverberation and adaptation yields a relative improvement of about 35% in terms of word error rate (WER) compared to the original signal. KW - Speech Recognition Y1 - 2014 PB - VDE VERLAG GMBH ER - TY - CHAP A1 - Ghahremani, Pegah A1 - BabaAli, Bagher A1 - Povey, Daniel A1 - Riedhammer, Korbinian A1 - Trmal, Jan A1 - Khudanpur, Sanjeev T1 - A Pitch Extraction Algorithm Tuned for Automatic Speech Recognition T2 - 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Florence, Italy, May 2014. N2 - In this paper we present an algorithm that produces pitch and probability-of-voicing estimates for use as features in automatic speech recognition systems. These features give large performance improvements on tonal languages for ASR systems, and even substantial improvements for non-tonal languages. Our method, which we are calling the Kaldi pitch tracker (because we are adding it to the Kaldi ASR toolkit), is a highly modified version of the getf0 (RAPT) algorithm. Unlike the original getf0 we do not make a hard decision whether any given frame is voiced or unvoiced; instead, we assign a pitch even to unvoiced frames while constraining the pitch trajectory to be continuous. Our algorithm also produces a quantity that can be used as a probability of voicing measure; it is based on the normalized autocorrelation measure that our pitch extractor uses. We present results on data from various languages in the BABEL project, and show a large improvement over systems without tonal features and systems where pitch and POV information was obtained from SAcC or getf0. KW - Automatic Speech Recognition Y1 - 2014 PB - IEEE ER - TY - CHAP A1 - Bocklet, Tobias A1 - Maier, Andreas A1 - Riedhammer, Korbinian A1 - Eysholdt, Ulrich A1 - Nöth, Elmar T1 - Erlangen-CLP: A Large Annotated Corpus of Speech from Children with Cleft Lip and Palate. T2 - Language Resources and Evaluation Conference (LREC), Reykjavik, Iceland, May 2014. N2 - In this paper we describe Erlangen-CLP, a large speech database of children with Cleft Lip and Palate. More than 800 German children with CLP (most of them between 4 and 18 years old) and 380 age matched control speakers spoke the semi-standardized PLAKSS test that consists of words with all German phonemes in different positions. So far 250 CLP speakers were manually transcribed, 120 of these were analyzed by a speech therapist and 27 of them by four additional therapists. The tharapists marked 6 different processes/criteria like pharyngeal backing and hypernasality which typically occur in speech of people with CLP. We present detailed statistics about the the marked processes and the inter-rater agreement. KW - Cleft Lip and palate KW - pathologic speech KW - Children's Speech Y1 - 2014 ER - TY - CHAP A1 - Wegmann, Steven A1 - Faria, Arlo A1 - Janin, Adam A1 - Riedhammer, Korbinian A1 - Morgan, Nelson T1 - The Tao of ATWV: Probing the mysteries of keyword search performance T2 - IEEE Workshop on Automatic Speech Recognition and Understanding (ASRU), Olomouc, Czech Republic, Dezember 2013. N2 - In this paper we apply diagnostic analysis to gain a deeper understanding of the performance of the the keyword search system that we have developed for conversational telephone speech in the IARPA Babel program. We summarize the Babel task, its primary performance metric, “actual term weighted value” (ATWV), and our recognition and keyword search systems. Our analysis uses two new oracle ATWV measures, a bootstrap-based ATWV confidence interval, and includes a study of the underpinnings of the large ATWV gains due to system combination. This analysis quantifies the potential ATWV gains from improving the number of true hits and the overall quality of the detection scores in our system's posting lists. It also shows that system combination improves our systems' ATWV via a small increase in the number of true hits in the posting lists. KW - Speech Recognition Y1 - 2013 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Gropp, Martin A1 - Bocklet, Tobias A1 - Hönig, Florian A1 - Nöth, Elmar A1 - Steidl, Stefan T1 - LMELectures: A Multimedia Corpus of Academic Spoken English T2 - First Workshop on Speech, Language and Audio in Multimedia (SLAM 2013), Marseille, France, August 2013, ISCA Archive. N2 - 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. KW - corpus description KW - academic spoken English KW - e-learning Y1 - 2013 SP - 102 EP - 107 ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Hai Do, Van A1 - Hieronymus, James T1 - A Study on LVCSR and Keyword Search for Tagalog T2 - INTERSPEECH 2013, 14th Annual Conference of the International Speech Communication Association (ISCA), Lyon, France, August 2013. N2 - We describe a state-of-the-art large vocabulary continuous speech recognition (LVCSR) and keyword search (KWS) system trained on roughly 70 hours of conversational telephone speech. Using the Kaldi speech recognition toolkit, we investigate several aspects: for the acoustic front-end, we analyze the use of mel-frequency cepstral coefficients (MFCC), pitch and probability-of-voicing (PoV), and deep neural network (DNN) bottleneck (BN) features, as well as their feature-level combination ("tandem"). For the acousticphonetic decision tree, we explore different hidden Markov model (HMM) topologies for the glottalization phoneme /?/ to model its typically short duration. For the acoustic model, we compare regular continuous HMM with a sort of multi-codebook subspace Gaussian mixture model (SGMM) that lead to an overall best word error rate (WER) of 58.7% and 56.3%, respectively. The KWS is implemented as a word lattice search, and is augmented by a syllable lattice back-up search to capture out-of-vocabulary keywords as well as misrecognized lexical surface forms due to ambiguous prefix and hyphenation rules. KW - Speech Recognition KW - keyword spotting Y1 - 2013 ER - TY - CHAP A1 - Bocklet, Tobias A1 - Riedhammer, Korbinian A1 - Eysholdt, Ulrich A1 - Nöth, Elmar T1 - Automatic Phoneme Analysis in Children with Cleft Lip and Palate T2 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), Vancouver, BC, Canada, May 2013. N2 - Cleft Lip and Palate (CLP) is among the most frequent congenital abnormalities. The impaired facial development affects the articulation, with different phonemes being impacted inhomogeneously among different patients. This work focuses on automatic phoneme analysis of children with CLP for a detailed diagnosis and therapy control. In clinical routine, the state-of-the-art evaluation is based on perceptual evaluations. Perceptual ratings act as ground-truth throughout this work, with the goal to build an automatic system that is as reliable as humans. We propose two different automatic systems focusing on modeling the articulatory space of a speaker: one system models a speaker by a GMM, the other system employs a speech recognition system and estimates fMLLR matrices for each speaker. SVR is then used to predict the perceptual ratings. We show that the fMLLR-based system is able to achieve automatic phoneme evaluation results that are in the same range as perceptual inter-rater-agreements. KW - Pathology KW - automatic assessment KW - spectral features KW - GMM KW - fMLLR Y1 - 2013 SP - 7572 EP - 7576 PB - IEEE ER - TY - CHAP A1 - Riedhammer, Korbinian A1 - Gropp, Martin A1 - Nöth, Elmar T1 - The FAU Video Lecture Browser System T2 - 2012 IEEE Spoken Language Technology Workshop (SLT), Miami, FL, USA, December 2012. N2 - 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. KW - automatic speech recognition KW - key phrase extraction KW - key phrase ranking KW - visualization KW - user interaction Y1 - 2012 SP - 392 EP - 397 PB - IEEE ER - TY - CHAP A1 - Hönig, Florian A1 - Bocklet, Tobias A1 - Riedhammer, Korbinian A1 - Batliner, Anton A1 - Nöth, Elmar T1 - The Automatic Assessment of Non-native Prosody: Combining Classical Prosodic Analysis with Acoustic Modelling T2 - INTERSPEECH 2012, 13th Annual Conference of the International Speech Communication Association (ISCA), Portland, OR, USA, September 2012. N2 - In earlier studies, we assessed the degree of non-nativeness employing prosodic information. In this paper, we combine prosodic information with (1) features derived from a Gaussian Mixture Model used as Universal Background Model (GMM-UBM), a powerful approach used in speaker identification, and (2) openSMILE, a standard open-source toolkit for extracting acoustic features. We evaluate our approach with English speech from 94 non-native speakers. GMM-UBM or openSMILE modelling alone yields lower performance than our prosodic feature vector; however, adding information from the GMM-UBM modelling or openSMILE by late fusion improves results. KW - computer-assisted language learning KW - non-native prosody KW - rhythm KW - automatic assessment Y1 - 2012 ER - 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 -