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Comparative Study And New Approach Multi Classifiers: Application To The Recognition Of Arabic Numerals

Mohamed KARIM Abdelmajid LAMKADAM
2016 Zenodo  
In fact, the task at first is devoted to study and present the different classifications algorithms (classifiers) and fly on the theoretical basis of algorithms recognition, which allows us to address  ...  Generally, most of the problems of recognition are due to the classification of the feature vectors, or to the mismatch between learning conditions and test, so to improve the robustness of the existing  ...  in HMM.  HMM-GMM [19] : Combination is very popular for its ease of implementation and easy of interpretation.  HMM-ANN [23] : ANN were used to estimate the emission probabilities of the HMM, done  ... 
doi:10.5281/zenodo.54645 fatcat:oofg56d7nfap3ky5cakrjglwhi

A Comparitive Survey of ANN and Hybrid HMM/ANN Architectures for Robust Speech Recognition

Mondher Frikha, Ahmed Ben Hamida
2012 American Journal of Intelligent Systems  
Such structure combines strength of Hidden Markov Models (HMM) in modeling stochastic sequences and the non-linear classification capability of Artificial Neural Networks (ANN).  ...  Finally, the robustness of the systems is evaluated by using a new preprocessing stage for denoising based on wavelet transform.  ...  Conclusions In this research, we described three acoustical modeling approaches, HMM, ANN and hybrid HMM/ANN, used in state of the art speech recognition systems.  ... 
doi:10.5923/j.ajis.20120201.01 fatcat:4zwuv6pftrenblw67hyhzlb46m

A Hybrid HMM/SVM Classifier for Wavelet Front End Robust Automatic Speech Recognition

Rajeswari Rajeswari, N. N. S. S. R. K. Prasad, Sathyanarayana V
2013 International Journal of Computer Applications  
Experiments indicate that for large vocabulary the classification power of SVMs and the elegant iterative training algorithms for the estimation of HMMs together as a hybrid classifier with the wavelet  ...  This paper discusses a hybrid classifier that harness the power of hidden markov models (HMM) and the discriminative support vector machines (SVM) applied to a wavelet front end based automatic speech  ...  ACKNOWLEDGEMENTS We would like to express our sincere thanks to Aeronautical Development Agency, (Ministry of Defence, Govt. of India), Bangalore, India for supporting to do our research work. 9.  ... 
doi:10.5120/13194-0856 fatcat:zq7drpu27vbgplc42w6zpxc5nq

A selection method of speech vocabulary for human-robot speech interaction

Hong Liu, Xiaofei Li
2010 2010 IEEE International Conference on Systems, Man and Cybernetics  
The algorithm for computing Word Robustness is given based on Hidden Markov Model (HMM), then the most robust sub-vocabulary can be selected based on it.  ...  Speech is the most natural and efficient way for Human-Robot Interaction (HRI), although speech recognition systems face some challenges on a mobile robot platform due to the wide range of users and varied  ...  HMM (Hidden Markov Model) and ANN (Artificial Neural Network) were used to ASR in the 1980s. ANN was always used with other methods such as ANN/HMM [4] .  ... 
doi:10.1109/icsmc.2010.5641975 dblp:conf/smc/LiuL10 fatcat:mbnkvnrnjnga5gv7f4mqxi4glu

A Robust Isolated Automatic Speech Recognition System using Machine Learning Techniques

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
The last section of paper covers the results obtained by using proposed approaches in which SVM, ANN with Cuckoo search algorithm and ANN with back propagation classifier is used.  ...  The focus is also on the improvement of pre-processing and feature extraction processes.  ...  On automatic Gujarati speech recognition a hybrid HMM/ANN approach is implemented by Sanjay Valaki, et.al, (2017) along with the combination of classification method and different feature extraction techniques  ... 
doi:10.35940/ijitee.j8765.0881019 fatcat:n7vfdkeehfavzf2utjlpuggiui

Robust Speech Recognition Using Fusion Techniques and Adaptive Filtering

Al-Haddad
2009 American Journal of Applied Sciences  
Robustness is a key issue in speech recognition. The algorithm is tested on speech samples that are a part of a Malay corpus.  ...  Accuracy of 94% on pattern recognition was obtainable using fusion HMM and DTW compared to 80.5% using DTW and 90.7% using HMM separately.  ...  There are a few types of fusion in speech recognition amongst them are HMM and Artificial Neural Network (ANN) [11] and HMM and Bayesian Network (BN) [12] .  ... 
doi:10.3844/ajassp.2009.290.295 fatcat:q5r4i33vyzcxlclia4toykkfgm

Robust Speech Recognition Using Fusion Techniques and Adaptive Filtering

S.A.R. Al-Haddad, S.A. Samad, A. Hussain, K.A. Ishak, A.O.A. Noor
2009 American Journal of Applied Sciences  
Robustness is a key issue in speech recognition. The algorithm is tested on speech samples that are a part of a Malay corpus.  ...  Accuracy of 94% on pattern recognition was obtainable using fusion HMM and DTW compared to 80.5% using DTW and 90.7% using HMM separately.  ...  There are a few types of fusion in speech recognition amongst them are HMM and Artificial Neural Network (ANN) [11] and HMM and Bayesian Network (BN) [12] .  ... 
doi:10.3844/ajas.2009.290.295 fatcat:dc4yip2lqzdrvhtdsovqgajc5y

Improving the Recognition Rate of Phonetic Arabic Letters Via Artificial Intelligent

Z Aly, E Mohamed, I Zedanc
2020 Egyptian Journal for Engineering Sciences and Technology  
An effective and robust method is proposed to evaluate speech feature to improve the performance the recognition accuracy.  ...  It is very important to enhance the recognition accuracy of the Arabic spoken letters. The accuracy of recognition system is affected by the feature extraction and the used classifier.  ...  The recognition system based on ANN achieved a recognition rate of 99.5% in the case of multi-speaker mode and 94.4% in the case of independent mode.  ... 
doi:10.21608/eijest.2020.97331 fatcat:dlfi22s3gndmbisppfy3luntnm

A Cross-Entropy-Guided (CEG) Measure for Speech Enhancement Front-End Assessing Performances of Back-End Automatic Speech Recognition

Li Chai, Jun Du, Chin-Hui Lee
2019 Interspeech 2019  
One challenging problem of robust automatic speech recognition (ASR) is how to measure the goodness of a speech enhancement algorithm without calculating word error rate (WER) due to the high costs of  ...  calculation between the high-level representations of clean and enhanced speech.  ...  vector of the clean speech and enhanced speech for the n-th frame, respectively and θ is a set of parameters of the ANN-HMM based acoustic model of ASR system.  ... 
doi:10.21437/interspeech.2019-2511 dblp:conf/interspeech/0002DL19a fatcat:oenn7yqf6rcrtj6v57n5op4uwq

A survey of hybrid ANN/HMM models for automatic speech recognition

Edmondo Trentin, Marco Gori
2001 Neurocomputing  
Then we focus on ANNs to estimate posterior probabilities of the states of an HMM and on'globala optimization, where a single, overall training criterion is de"ned over the HMM and the ANNs.  ...  The goal in hybrid systems for ASR is to take advantage from the properties of both HMMs and ANNs, improving #exibility and recognition performance. A variety of di!  ...  Acknowledgements The authors wish to acknowledge Renato De Mori and Yoshua Bengio for their unvaluable contributions, Fabio Brugnara for his trellis artwork, and two anonymous reviewers of Neurocomputing  ... 
doi:10.1016/s0925-2312(00)00308-8 fatcat:bkjdthljuzh67mhxufphghule4

The Summarize of Improved HMM Model

Fang Fang Shi, Xian Yi Cheng, Xiang Chen
2013 Advanced Materials Research  
The hidden markov model is a kind of important probability model of series data processing and statistical learning and it has been successfully applied in many engineering tasks.  ...  This paper introduces the basic principle of hidden markov model firstly, and then discusses the limitations of hidden markov model, as well as the improved hidden markov model which is put forward to  ...  ACKNOLEDGEMENT This work is supported by Natural Science Foundation of China National (No: 61202006)  ... 
doi:10.4028/www.scientific.net/amr.756-759.3384 fatcat:yvnxi5li5nacdkgnmbubadiwau

Re-evaluation of LVQ-HMM hybrid algorithm

Hitoshi Iwamida, Shigeru Katagiri, Erik McDermott
1993 Journal of the Acoustical Society of Japan (E)  
However, the performance of LVQ-HMM has been less striking in more difficult, large scale speech recognition situations, making evaluation of the algorithm controversial and suggesting a more detailed  ...  The LVQ-HMM hybrid algorithm was one of the first algorithms proposed in a recent approach aiming to integrate a highly discriminative artificial neural network-based classifier with an HMM capable of  ...  Toshiyuki Hana zawa of the ATR Interpreting Telephony Research Laboratories (currently Mitsubishi Electrical Cor poration)for his help in using the HMM-LR soft -ware.  ... 
doi:10.1250/ast.14.267 fatcat:5lvmscxmk5grdgw3y4nqd2unr4

Discriminative training for speech recognition

Yoh'ichi Tohkura
1992 Journal of the Acoustical Society of Japan (E)  
Motivated by earlier work on LVQ2 and its applications to speech recognition, LVQ and related topics came to more than one third of the papers presented at a poster session for speech rec ognition in the  ...  The recent advent of artificial neural networks (ANN) and learning vector quantization (LVQ), and their good performance in speech recognition tasks, has revived an interest in the discriminative training  ...  Motivated by earlier work on LVQ2 and its applications to speech recognition, LVQ and related topics came to more than one third of the papers presented at a poster session for speech rec ognition in the  ... 
doi:10.1250/ast.13.331 fatcat:gm65fwyk4bfojlvsf5ltw2c6mi

A REVIEW ON SPEECH EMOTION FEATURES

Noor Aina Zaidan, Md Sah Hj. Salam
2015 Jurnal Teknologi  
The recognition rate of emotion in speech signal is inconsistent depending on the features used in the experiment and also the database itself.  ...  The finding of reliable speech features is an ongoing research.  ...  Artificial Neural Networks (ANN) is one of the approaches in the field of recognition and has been used in the fields of research including speech recognition field.  ... 
doi:10.11113/jt.v75.4988 fatcat:dyufqneibbe7pbz3inochxo3pu

Acoustics-guided evaluation (AGE): a new measure for estimating performance of speech enhancement algorithms for robust ASR [article]

Li Chai, Jun Du, Chin-Hui Lee
2018 arXiv   pre-print
One challenging problem of robust automatic speech recognition (ASR) is how to measure the goodness of a speech enhancement algorithm (SEA) without calculating the word error rate (WER) due to the high  ...  AGE calculation between the representations of clean speech and degraded speech.  ...  and θ is the set of parameters of the ANN-HMM based AM.  ... 
arXiv:1811.11517v1 fatcat:d62hmmdhrngazevy4q64j4mrqq
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