Segmented-Memory Recurrent Neural Networks versus Hidden Markov Models in Emotion Recognition from Speech
暂无分享,去创建一个
[1] Gunnar Fant,et al. Acoustic Theory Of Speech Production , 1960 .
[2] Chun Chen,et al. A robust multimodal approach for emotion recognition , 2008, Neurocomputing.
[3] L. Baum,et al. A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains , 1970 .
[4] Friedhelm Schwenker,et al. Maximum Echo-State-Likelihood Networks for Emotion Recognition , 2010, ANNPR.
[5] Biing-Hwang Juang,et al. Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.
[6] Andreas Wendemuth,et al. Processing affected speech within human machine interaction , 2009, INTERSPEECH.
[7] Jeffrey L. Elman,et al. Finding Structure in Time , 1990, Cogn. Sci..
[8] Andreas Wendemuth,et al. Determining optimal signal features and parameters for HMM-based emotion classification , 2010, Melecon 2010 - 2010 15th IEEE Mediterranean Electrotechnical Conference.
[9] Björn W. Schuller,et al. Recognising realistic emotions and affect in speech: State of the art and lessons learnt from the first challenge , 2011, Speech Commun..
[10] Kazuyuki Shinohara,et al. Discrimination between mothers’ infant- and adult-directed speech using hidden Markov models , 2011, Neuroscience Research.
[11] Ronald J. Williams,et al. Gradient-based learning algorithms for recurrent networks and their computational complexity , 1995 .
[12] Björn W. Schuller,et al. On the Influence of Phonetic Content Variation for Acoustic Emotion Recognition , 2008, PIT.
[13] Günther Palm,et al. Real-Time Emotion Recognition Using Echo State Networks , 2008, PIT.
[14] Van Nostrand,et al. Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm , 1967 .
[15] Andreas Wendemuth,et al. Heading toward to the natural way of human-machine interaction: the nimitek project , 2009, 2009 IEEE International Conference on Multimedia and Expo.
[16] Shrikanth S. Narayanan,et al. Primitives-based evaluation and estimation of emotions in speech , 2007, Speech Commun..
[17] Fakhri Karray,et al. Speech Emotion Recognition using Gaussian Mixture Vector Autoregressive Models , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.
[18] Valery A. Petrushin,et al. Emotion recognition in speech signal: experimental study, development, and application , 2000, INTERSPEECH.
[19] John S. Boreczky,et al. A hidden Markov model framework for video segmentation using audio and image features , 1998, Proceedings of the 1998 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP '98 (Cat. No.98CH36181).
[20] Vyacheslav P. Tuzlukov,et al. Signal detection theory , 2001 .
[21] Ryohei Nakatsu,et al. Emotion Recognition in Speech Using Neural Networks , 2000, Neural Computing & Applications.
[22] Oudeyer Pierre-Yves,et al. The production and recognition of emotions in speech: features and algorithms , 2003 .
[23] Björn W. Schuller,et al. The INTERSPEECH 2009 emotion challenge , 2009, INTERSPEECH.
[24] Nikos Fakotakis,et al. Comparative Evaluation of Various MFCC Implementations on the Speaker Verification Task , 2007 .
[25] A. Mehrabian. Pleasure-arousal-dominance: A general framework for describing and measuring individual differences in Temperament , 1996 .
[26] Björn W. Schuller,et al. Acoustic emotion recognition: A benchmark comparison of performances , 2009, 2009 IEEE Workshop on Automatic Speech Recognition & Understanding.
[27] Meinard Müller,et al. Information retrieval for music and motion , 2007 .
[28] Andrew J. Viterbi,et al. Error bounds for convolutional codes and an asymptotically optimum decoding algorithm , 1967, IEEE Trans. Inf. Theory.
[29] Björn W. Schuller,et al. Speech emotion recognition combining acoustic features and linguistic information in a hybrid support vector machine-belief network architecture , 2004, 2004 IEEE International Conference on Acoustics, Speech, and Signal Processing.
[30] N. Burgess,et al. Temporal Grouping Effects in Immediate Recall: A Working Memory Analysis , 1996 .
[31] Astrid Paeschke,et al. A database of German emotional speech , 2005, INTERSPEECH.
[32] Björn W. Schuller,et al. Abandoning emotion classes - towards continuous emotion recognition with modelling of long-range dependencies , 2008, INTERSPEECH.
[33] H Hermansky,et al. Perceptual linear predictive (PLP) analysis of speech. , 1990, The Journal of the Acoustical Society of America.
[34] Yoshua Bengio,et al. Learning long-term dependencies with gradient descent is difficult , 1994, IEEE Trans. Neural Networks.
[35] P. Ekman. Are there basic emotions? , 1992, Psychological review.
[36] Steve Young,et al. The HTK book version 3.4 , 2006 .
[37] Narendra S. Chaudhari,et al. Segmented-Memory Recurrent Neural Networks , 2009, IEEE Transactions on Neural Networks.
[38] Andreas Wendemuth,et al. A Simple Recurrent Network for Implicit Learning of Temporal Sequences , 2010, Cognitive Computation.
[39] Diego H. Milone,et al. Spoken emotion recognition using hierarchical classifiers , 2011, Comput. Speech Lang..
[40] Albino Nogueiras,et al. Speech emotion recognition using hidden Markov models , 2001, INTERSPEECH.
[41] David Philippou-Hübner,et al. Determining optimal features for emotion recognition from speech by applying an evolutionary algorithm , 2010, INTERSPEECH.
[42] Fakhri Karray,et al. Survey on speech emotion recognition: Features, classification schemes, and databases , 2011, Pattern Recognit..
[43] Marilyn K. Rigby,et al. Influence of digit grouping on memory for telephone numbers. , 1963 .
[44] Sepp Hochreiter,et al. The Vanishing Gradient Problem During Learning Recurrent Neural Nets and Problem Solutions , 1998, Int. J. Uncertain. Fuzziness Knowl. Based Syst..
[45] Andreas Wendemuth,et al. Implicit Sequence Learning - A Case Study with a 4-2-4 Encoder Simple Recurrent Network , 2010, IJCCI.
[46] Friedhelm Schwenker,et al. A Hidden Markov Model Based Approach for Facial Expression Recognition in Image Sequences , 2010, ANNPR.
[47] Constantine Kotropoulos,et al. Emotional speech recognition: Resources, features, and methods , 2006, Speech Commun..
[48] John H. L. Hansen,et al. Angry emotion detection from real-life conversational speech by leveraging content structure , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.
[49] R.G. Shiavi,et al. Distinguishing depression and suicidal risk in men using GMM based frequency contents of affective vocal tract response , 2008, 2008 International Conference on Control, Automation and Systems.