Notes:
Probabilistic neural networks (PNNs) are a type of artificial neural network that is used for tasks that involve uncertainty or probabilistic reasoning. They are based on the idea of using probability theory to model the uncertainty of neural network predictions, and they are often used in situations where the relationships between variables are complex or nonlinear.
PNNs are used in a variety of applications, including classification, regression, and prediction tasks. They are particularly well-suited for tasks that involve uncertain or noisy data, or that involve complex or nonlinear relationships between variables.
In the context of dialog systems, PNNs can be used to model and predict the likelihood of different responses or actions based on the input and context of the conversation. For example, a PNN-based dialog system might use probability theory to determine the most likely response to a user’s input based on the context of the conversation and the system’s past responses.
Wikipedia:
See also:
100 Best GitHub: Deep Learning | 100 Best Neural Network Videos | Holographic Neural Technology | Neural Networks In Dialog Systems
INSPIRE: Evaluation of a smart-home system for infotainment management and device control S Möller, J Krebber, A Raake, P Smeele… – arXiv preprint cs/ …, 2004 – arxiv.org … References Ganchev, T., Fakotakis, N., Kokkinakis, G. (2002). A Speaker Verification System Based on Probabilistic Neural Networks. In Proc. … Möller, S. (2004). A New ITU-T Recommendation on the Evaluation of Telephone-Based Spoken Dialogue Systems. In Proc. … Cited by 33 Related articles All 18 versions Cite Save
Online learning of objects in a biologically motivated visual architecture H Wersing, S Kirstein, M Götting, H Brandl… – … Journal of Neural …, 2007 – World Scientific … 13 Li et al. have presented a system for interactive object learning on a mobile robot that features an elaborated multi-modal dialogue system to enable context-dependent attention selection using speech Page 3. 2 July 29, 2007 21:53 00108 … Cited by 23 Related articles All 19 versions Cite Save
Gesture components for natural interaction with in-car devices M Zobl, R Nieschulz, M Geiger, M Lang… – … -Based Communication in …, 2004 – Springer … Fig. 8. Recognition rate of the probabilistic neural network used in the first stage of the help system Page 10. … (2000) 462–467 5. Morguet, P., Lang, M.: Comparison of approaches to continuous hand gesture recognition for a visual dialog system. In: Proceedings, ICASP 1999 Int. … Cited by 12 Related articles All 15 versions Cite Save
Speech recognition in the Waxholm dialog system M Blomberg, K Elenius, N Ström – Lund Working Papers in …, 2009 – journals.lub.lu.se … K., Granström, B., Gustafson, J., Hunnicutt, S., Lindeli, R., and Neovius, L. (1993): “An experimental dialog system: WAXHOLM,” Proceedings of … Elenius K. & Traven H. (1993): “Multi-layer perceptrons and probabilistic neural networks for phoneme recognition,” Proceedings of … Cited by 2 Related articles All 10 versions Cite Save More
Classification on speech emotion recognition-a comparative study T Iliou, CN Anagnostopoulos – … Journal on Advances in Life Sciences, 2010 – thinkmind.org … In the speaker dependent framework, Probabilistic Neural Network reaches very high accuracy(94%), while in the speaker independent framework the classification … For example a dialog system might modulate its speech to be more puerile if it deems the emotional model of … Cited by 9 Related articles All 3 versions Cite Save
A comparative study of gender and age classification in speech signals MH Sedaaghi – Iranian Journal of Electrical & Electronic Engineering, 2009 – 198.55.49.74 … The Bayes classifier using sequential floating forward selection (SFFS) for feature selection, probabilistic Neural Networks (PNNs), support vector machines (SVMs), the K nearest neighbor (K-NN) and Gaussian mixture model (GMM), as different classifiers, are empirically … Cited by 13 Related articles All 6 versions Cite Save More
SVM-MLP-PNN classifiers on speech emotion recognition field-A comparative study T Iliou, CN Anagnostopoulos – … (ICDT), 2010 Fifth International …, 2010 – ieeexplore.ieee.org … In speaker dependent framework, Probabilistic Neural Network classifier reached very high accuracy of 94%, whereas in speaker independent framework, Support Vector … For example a dialog system might modulate its speech to be more puerile if it deems the emotional model … Cited by 5 Related articles All 4 versions Cite Save
Gender Classification in Speech Recognition using Fuzzy Logic and Neural Network. K Meena, K Subramaniam… – … Arab Journal of …, 2013 – search.ebscohost.com … the Bayes classifier using various techniques Sequential Floating Forward Selection (SFFS) for feature selection, probabilistic Neural Networks (PNNs), Support … of speaker’s gender by her/his voice has been an important aspect for achieving high-quality dialogue systems. … Cited by 4 Related articles All 9 versions Cite Save
Negative Emotional State Detection from Speech P Zervas, T Ganchev, N Fakotakis – … on Communication systems, …, 2006 – wcl.ece.upatras.gr … speech interaction system for a smart home environment, Detecting negative emotional states, would make the spoken dialogue system capable to … rapidly ex- tracted on-line; and (d) two different classification tech- niques have been utilized: Probabilistic Neural Network [9] and … Cited by 1 Related articles Cite Save More
Improved Malay vowel feature extraction method based on first and second formants AMY Shahrul, F Siraj, S Yaacob… – Computational …, 2010 – ieeexplore.ieee.org … USM experimented with 200 vowel signals using wavelet de- noising approach and Probabilistic Neural Network Model [13]. … research workshop on Perception and Interactive Technologies for Speech- Based Systems: Perception in Multimodal Dialogue Systems Kloster Irsee … Cited by 2 Related articles All 4 versions Cite Save
Interactive Dialogue for Behavior Teaching to Robots based on Primitive Behaviors with Fuzzy Voice Commands B Jayasekara, K Watanabe… – Information and Automation …, 2008 – ieeexplore.ieee.org … the player. A probabilistic neural network was used to implement it and used in positioning example [14]. In addition … the user. The interactive dialogue system is handled by the IM. The functional overview of the IM is shown in Fig. 3. It … Cited by 1 Related articles Cite Save
A flexible bio-affective gaming interface J Arroyo-Palacios, DM Romano – 2010 – staffwww.dcs.shef.ac.uk … the user. The best results were obtained with a probabilistic neural network with accuracy results of 84.46% on the training data and 78.38% on the validation for new independent data sets. 1.- INTRODUCTION Physiological … Cited by 1 Related articles Cite Save More
Age Group Estimation based on Acoustic Analysis of Speech DK Yadav, K Malhotra, A Khosl – 2010 – desceco.org … Two approaches based on Gaussian Mixture Models (GMM) and Probabilistic Neural Networks (PNN) were tried. … On the other hand, most of the present day spoken dialogue systems deal with different users in similar fashion in spite of the fact that most of the users have … Related articles Cite Save More
[BOOK] Artificial Intelligence: Theories, Models and Applications 7th Hellenic Conference on AI, SETN 2012, Lamia, Greece, May 28-31, 2012, Proceedings I Maglogiannis, V Plagianakos, I Vlahavas – 2012 – dl.acm.org All 2 versions Cite Save
A novel MFCC approach for Speaker Identification using BPNN K Dash, S Sahu, BD Panda – rspublication.com … In Speaker verification integrated within a dialog system, if biometric authentication is desired in combination with a dialog system that performs automatic speech recognition, a third kind of Page 9. … “Generalized locally recurrent probabilistic neural networks with … Related articles Cite Save
Theories and Applications IMV Plagianakos, I Vlahavas – 2012 – Springer … and George Tsatsaronis Parallelism, Localization and Chain Gradient Tuning Combinations for Fast Scalable Probabilistic Neural Networks in Data … and Ilias Maglogiannis Special Session: Intelligent, Affective, and Natural Interfaces An Adaptive Dialogue System with Online … Cite Save
Fuzzy logic and neural network based gender classification using three features K Meena, KR Subramaniam, M Gomathy – International Journal of …, 2014 – Inderscience … Using Sequential Floating Forward Selection (SFFS) for feature selection, Probabilistic Neural Networks (PNNs), Support Vector Machines (SVMs), the K nearest neighbour (K-NN) and Gaussian Mixture Model (GMM), as different … For achieving high-quality dialogue systems. … Cite Save
Speech & Language R & D Activity at the Wire Communications Laboratory G Kokkinakis – wcl.ece.upatras.gr … of moving speakers, text dependent and independent speaker recognition, speech coding and most recently to dialog systems over the … Recently a text-independent speaker verification system, the WCL-1 was developed, based on Probabilistic Neural Networks (PNN) [37, 38 … Related articles Cite Save More
Established Methods L Baghai-Ravary, SW Beet – Automatic Speech Signal Analysis for Clinical …, 2013 – Springer … science, vol 4188, pp 589–596. Hariharan M, Paulraj MP, Yaacob S (2010) Time-domain features and probabilistic neural network for the … Accessed 16 Feb 2012. Reilly RB, Moran R, Lacy PD (2004) Voice pathology assessment based on a dialogue system and speech analysis. … Related articles All 2 versions Cite Save
Vision based Traffic Police Hand Signal Recognition in Surveillance Video-A Survey. R Sathya, MK Geetha – International Journal of Computer …, 2013 – search.ebscohost.com … network. BPNN structure is input layer, Hidden layer and output layer. Probabilistic neural network (PNN) is a feed- forward neural network that implements a Bayesian decision strat- egy for classifying input vectors. Artificial … Related articles All 2 versions Cite Save
EMSys: An Emotion Monitoring System for Call Center Agents PFO Boco, DKB Tercias, KRD Cruz, CR Raquel… – Citeseer … [3] L. Cen, W. Ser, Z. Yu, Speech Emotion Recognition Using Canonical Correlation Analysis and Probabilistic Neural Network, Seventh International … [15] J. Pittermann, A. Pittermann, Integrating Emotion Recognition into an Adaptive Spoken Language Dialogue System, Dept. … Related articles Cite Save More
A Natural Language Model of Computing with Words in Web Pages Z Ze-yu, Z Ping – aclweb.org … Fig. 1. Components of the mixed initiative dialogue system in Internet 2 Language for Research in Web Pages … In reality, there are many significant computational models such as probabilistic neural networks, residuated lattice-valued automata, quantum automata. … Related articles All 7 versions Cite Save More
A New Fangled Insinuation for Stress Affect Speech Classification NMTSCP Sumathi – 2010 – core.kmi.open.ac.uk … Keywords Affect Recognition, Speech analysis, Support vector machine (SVM), Probabilistic Neural Network(PNN), Hidden Markov Model(HMM). … The features are fed into a five state Hidden Markov mathematical Model(HMM) and a Probabilistic Neural Network(PNN). … Related articles All 3 versions Cite Save More
State of Research of Speech Recognition M Sarma, KK Sarma – … -Based Speech Segmentation using Hybrid Soft …, 2014 – Springer … 15. A work in 2005 reported by Yousefian and Analoui presents an approach to check the applicability of a special model of radial basis probabilistic neural networks (RBPNN) as a classifier for speech recognition. … [ 69 ] where a spoken dialog system is designed to use in … Cite Save
A literature review on artificial intelligence SA Oke – International Journal of Information and Management …, 2008 – ijims.ms.tku.edu.tw … dialogue policy, which address the technical challenges in applying reinforcement learn- ing to a working dialogue system with human users was presented (Singh et al., 2002). Page 14. i … perimental spoken dialogue system that provides users with access to information about … Cited by 4 Related articles All 2 versions Cite Save More
Noise Robustness Of First Formant Bandwidth (F1Bw) Features In Malay Vowel Recognition. M Yusuf, S Azmi, NI Mahat, F Siraj… – Journal of Information …, 2012 – search.ebscohost.com … an experiment on 200 vowel signals using the wavelet de-noising approach and the Probabilistic Neural Network Model. … IEEE tutorial and research workshop on Perception and Interactive Technologies for Speech-Based Systems: Perception in Multimodal Dialogue Systems. … Related articles Cite Save
Speaker recognition TD Ganchev – 2005 – wcl.ece.upatras.gr … 29 2.7. Characterization of the Probabilistic Neural Network …………… 32 2.8. … 118 5.5. Summary and discussion …………… 123 Chapter 6: Extensions of the Probabilistic Neural Network …………… 125 6.1. … Cited by 24 Related articles All 6 versions Cite Save More
Technology and Implementation L Baghai-Ravary, SW Beet – Automatic Speech Signal Analysis for Clinical …, 2013 – Springer … Med Eng Phys 24:419–429CrossRef. Hariharan M, Paulraj MP, Yaacob S (2010) Time-domain features and probabilistic neural network for the … PHONUS 3:143–153. Reilly RB, Moran R, Lacy PD (2004) Voice pathology assessment based on a dialogue system and speech … Related articles All 2 versions Cite Save
Hybrid Approach to Speech–Emotion Recognition J Pittermann, A Pittermann, W Minker – Handling Emotions in Human- …, 2010 – Springer … A multi-layer perceptron and a probabilistic neural network are compared in Dan-Ning Jiang (2004) where recognition rates of up to 94% are achieved for six emotions with the probabilistic neural network based on acoustic features. … Related articles All 2 versions Cite Save
A Software Testbed for Assessing Human-Robot Verbal Interaction H Bouraoui – 2010 – uwspace.uwaterloo.ca … However, the language usages of many of them were simple and may not be considered as full speech dialogue systems providing natural language understanding. … systems relies on using simple speech commands and may not be considered as full speech dialogue systems. … Related articles All 3 versions Cite Save
Robotic Forceps Operated by Voice Instructions in Fuzzy Coach-Player System K Izumi, K Watanabe, S Ishii… – ????????? ?? …, 2007 – isis2007.fuzzy.or.kr … J. Fry, F. Asano, Y. Motomura, I. Hara, T. Kurita, S. Hayamizu, and N. Yamasaki, “A speech dialogue system of the … C. Jayawardena, K. Watanabe, and K. Izumi, “Controlling a robot manipulator with fuzzy voice commands using a probabilistic neural network,” Neural Computing … Related articles All 3 versions Cite Save More
[BOOK] Automatic Speech Signal Analysis for Clinical Diagnosis and Assessment of Speech Disorders L Baghai-Ravary, SW Beet – 2012 – books.google.com … Some of the topics covered in this series include the presentation of real life commercial deployment of spoken dialog systems, con- temporary methods of speech parameterization, developments in information security for automated speech, forensic speaker recognition, use … Cited by 2 Related articles All 4 versions Cite Save
SpringerBriefs in Electrical and Computer Engineering Speech Technology A Neustein – Springer … Some of the topics covered in this series include the presentation of real life commercial deployment of spoken dialog systems, con- temporary methods of speech parameterization, developments in information security for automated speech, forensic speaker recognition, use … Related articles Cite Save
PRESTK: situation-aware presentation of messages and infotainment content for drivers C Endres – 2013 – scidok.sulb.uni-saarland.de Page 1. PRESTK: Situation-Aware Presentation of Messages and Infotainment Content for Drivers Dissertation zur Erlangung des Grades Doktor der Ingenieurwissenschaften (Dr.-Ing.) der Naturwissenschaftlich-Technischen Fakultät I der Universität des Saarlandes … Cited by 3 Related articles All 2 versions Cite Save
Short-term Time Series in Automatic Speech Processing R Timofte – 2007 – cs.joensuu.fi Page 1. Short-term Time Series in Automatic Speech Processing Radu Timofte MASTER’S THESIS University of Joensuu Department of Computer Science and Statistics PO Box 111, FIN-80101 Joensuu, Finland October 31, 2007 Page 2. ii Table of Contents … Related articles All 6 versions Cite Save More