| Database of multichannel in-ear and behind-the-ear head-related and binaural room impulse responses H Kayser, SD Ewert, J Anemüller, T Rohdenburg, V Hohmann, ... EURASIP Journal on advances in signal processing 2009, 1-10, 2009 | 416 | 2009 |
| Complex independent component analysis of frequency-domain electroencephalographic data J Anemüller, TJ Sejnowski, S Makeig Neural networks 16 (9), 1311-1323, 2003 | 259 | 2003 |
| Amplitude modulation decorrelation for convolutive blind source separation J Anemuller ICA 2000, 215-220, 2000 | 211 | 2000 |
| Monitoring and representing complex signals S Makeig, J Anemüller US Patent 7,254,500, 2007 | 158 | 2007 |
| Oldenburg logatome speech corpus (OLLO) for speech recognition experiments with humans and machines. T Wesker, BT Meyer, K Wagener, J Anemüller, A Mertins, B Kollmeier Interspeech, 1273-1276, 2005 | 109 | 2005 |
| Automatic acoustic siren detection in traffic noise by part-based models J Schröder, S Goetze, V Grützmacher, J Anemüller 2013 IEEE International Conference on Acoustics, Speech and Signal …, 2013 | 64 | 2013 |
| Spectro-temporal Gabor filterbank features for acoustic event detection J Schröder, S Goetze, J Anemüller IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (12 …, 2015 | 53 | 2015 |
| Beyond novelty detection: Incongruent events, when general and specific classifiers disagree D Weinshall, A Zweig, H Hermansky, S Kombrink, F Ohl, J Anemüller, ... IEEE Transactions on Pattern Analysis and Machine Intelligence 34 (10), 1886 …, 2012 | 51* | 2012 |
| An auditory inspired amplitude modulation filter bank for robust feature extraction in automatic speech recognition N Moritz, J Anemüller, B Kollmeier IEEE/ACM Transactions on Audio, Speech, and Language Processing 23 (11 …, 2015 | 50 | 2015 |
| A discriminative learning approach to probabilistic acoustic source localization H Kayser, J Anemüller 2014 14th International Workshop on Acoustic Signal Enhancement (IWAENC), 99-103, 2014 | 50 | 2014 |
| Amplitude modulation spectrogram based features for robust speech recognition in noisy and reverberant environments N Moritz, J Anemüller, B Kollmeier 2011 IEEE International Conference on Acoustics, Speech and Signal …, 2011 | 45 | 2011 |
| On-line blind separation of moving sound sources J Anemќller, T Gramss ICA, 1998 | 41 | 1998 |
| Classification of human cough signals using spectro-temporal Gabor filterbank features J Schröder, J Anemuller, S Goetze 2016 IEEE international conference on acoustics, speech and signal …, 2016 | 40 | 2016 |
| Robust speech detection in real acoustic backgrounds with perceptually motivated features JH Bach, J Anemüller, B Kollmeier Speech Communication 53 (5), 690-706, 2011 | 40 | 2011 |
| On the use of spectro-temporal features for the IEEE AASP challenge ‘detection and classification of acoustic scenes and events’ J Schröder, N Moritz, MR Schädler, B Cauchi, K Adiloglu, J Anemüller, ... 2013 IEEE Workshop on Applications of Signal Processing to Audio and …, 2013 | 38 | 2013 |
| Adaptive separation of acoustic sources for anechoic conditions: A constrained frequency domain approach J Anemüller, B Kollmeier Speech Communication 39 (1-2), 79-95, 2003 | 37 | 2003 |
| Spatio-temporal dynamics in fMRI recordings revealed with complex independent component analysis J Anemüller, JR Duann, TJ Sejnowski, S Makeig Neurocomputing 69 (13-15), 1502-1512, 2006 | 36 | 2006 |
| Across-frequency processing in convolutive blind source separation J Anemüller Universität Oldenburg, 2001 | 33 | 2001 |
| Modulation-based detection of speech in real background noise: Generalization to novel background classes JH Bach, B Kollmeier, J Anemüller 2010 IEEE International Conference on Acoustics, Speech and Signal …, 2010 | 32 | 2010 |
| Classifier architectures for acoustic scenes and events: implications for DNNs, TDNNs, and perceptual features from DCASE 2016 J Schröder, N Moritz, J Anemüller, S Goetze, B Kollmeier IEEE/ACM Transactions on Audio, Speech, and Language Processing 25 (6), 1304 …, 2017 | 28 | 2017 |
