Letteratura scientifica selezionata sul tema "MFCC"
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Articoli di riviste sul tema "MFCC"
Lankala, Srinija, e Dr M. Ramana Reddy. "Design and Implementation of Energy-Efficient Floating Point MFCC Extraction Architecture for Speech Recognition Systems". International Journal for Research in Applied Science and Engineering Technology 10, n. 9 (30 settembre 2022): 1217–25. http://dx.doi.org/10.22214/ijraset.2022.46807.
Testo completoChu, Yun Yun, Wei Hua Xiong, Wei Wei Shi e Yu Liu. "The Extraction of Differential MFCC Based on EMD". Applied Mechanics and Materials 313-314 (marzo 2013): 1167–70. http://dx.doi.org/10.4028/www.scientific.net/amm.313-314.1167.
Testo completoMohammed, Duraid Y., Khamis Al-Karawi e Ahmed Aljuboori. "Robust speaker verification by combining MFCC and entrocy in noisy conditions". Bulletin of Electrical Engineering and Informatics 10, n. 4 (1 agosto 2021): 2310–19. http://dx.doi.org/10.11591/eei.v10i4.2957.
Testo completoEskidere, Ömer, e Ahmet Gürhanlı. "Voice Disorder Classification Based on Multitaper Mel Frequency Cepstral Coefficients Features". Computational and Mathematical Methods in Medicine 2015 (2015): 1–12. http://dx.doi.org/10.1155/2015/956249.
Testo completoAbdul, Zrar Khalid. "Kurdish Spoken Letter Recognition based on k-NN and SVM Model". Journal of University of Raparin 7, n. 4 (30 novembre 2020): 1–12. http://dx.doi.org/10.26750/vol(7).no(4).paper1.
Testo completoRaychaudhuri, Aryama, Rudra Narayan Sahoo e Manaswini Behera. "Application of clayware ceramic separator modified with silica in microbial fuel cell for bioelectricity generation during rice mill wastewater treatment". Water Science and Technology 84, n. 1 (4 giugno 2021): 66–76. http://dx.doi.org/10.2166/wst.2021.213.
Testo completoHuizen, Roy Rudolf, e Florentina Tatrin Kurniati. "Feature extraction with mel scale separation method on noise audio recordings". Indonesian Journal of Electrical Engineering and Computer Science 24, n. 2 (1 novembre 2021): 815. http://dx.doi.org/10.11591/ijeecs.v24.i2.pp815-824.
Testo completoZhou, Ping, Xiao Pan Li, Jie Li e Xin Xing Jing. "Speech Emotion Recognition Based on Mixed MFCC". Applied Mechanics and Materials 249-250 (dicembre 2012): 1252–58. http://dx.doi.org/10.4028/www.scientific.net/amm.249-250.1252.
Testo completoSharma, Samiksha, Anupam Shukla e Pankaj Mishra. "Speech and Language Recognition using MFCC and DELTA-MFCC". International Journal of Engineering Trends and Technology 12, n. 9 (25 giugno 2014): 449–52. http://dx.doi.org/10.14445/22315381/ijett-v12p286.
Testo completoG., Rupali, e S. K. Bhatia. "Analysis of MFCC and Multitaper MFCC Feature Extraction Methods". International Journal of Computer Applications 131, n. 4 (17 dicembre 2015): 7–10. http://dx.doi.org/10.5120/ijca2015906883.
Testo completoTesi sul tema "MFCC"
Mukherjee, Rishiraj. "Speaker Recognition Using Shifted MFCC". Scholar Commons, 2012. http://scholarcommons.usf.edu/etd/4136.
Testo completoTolunay, Atahan. "Text-Dependent Speaker Verification Implemented in Matlab Using MFCC and DTW". Thesis, Linköpings universitet, Informationskodning, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-60992.
Testo completoKrotký, Jan. "Dekodér pro systém detekce klíčových slov". Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2009. http://www.nusl.cz/ntk/nusl-218176.
Testo completoMubarak, Omer Mohsin Electrical Engineering & Telecommunications Faculty of Engineering UNSW. "Speech and music discrimination using short-time features". Awarded by:University of New South Wales. Electrical Engineering & Telecommunications, 2006. http://handle.unsw.edu.au/1959.4/31954.
Testo completoPan, Linlin. "Research and simulation on speech recognition by Matlab". Thesis, Högskolan i Gävle, Avdelningen för elektronik, matematik och naturvetenskap, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:hig:diva-16950.
Testo completoSIQUEIRA, JAN KRUEGER. "CONTINUOUS SPEECH RECOGNITION WITH MFCC, SSCH AND PNCC FEATURES, WAVELET DENOISING AND NEURAL NETWORKS". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=19143@1.
Testo completoUm dos maiores desafios na área de reconhecimento de voz contínua é desenvolver sistemas robustos ao ruído aditivo. Para isso, este trabalho analisa e testa três técnicas. A primeira delas é a extração de atributos do sinal de voz usando os métodos MFCC, SSCH e PNCC. A segunda é a remoção de ruído do sinal de voz via wavelet denoising. A terceira e última é uma proposta original batizada de feature denoising, que busca melhorar os atributos extraídos usando um conjunto de redes neurais. Embora algumas dessas técnicas já sejam conhecidas na literatura, a combinação entre elas trouxe vários resultados interessantes e inéditos. Inclusive, nota-se que o melhor desempenho vem da união de PNCC com feature denoising.
One of the biggest challenges on the continuous speech recognition field is to develop systems that are robust to additive noise. To do so, this work analyses and tests three techniques. The first one extracts features from the voice signal using the MFCC, SSCH and PNCC methods. The second one removes noise from the voice signal through wavelet denoising. The third one is an original one, called feature denoising, that seeks to improve the extracted features using a set of neural networks. Although some of these techniques are already known in the literature, the combination of them brings many interesting and new results. In fact, it is noticed that the best performance comes from the union of PNCC and feature denoising.
Dobrovolskis, Martynas. "Šnekos atpažinimas". Master's thesis, Lithuanian Academic Libraries Network (LABT), 2005. http://vddb.library.lt/obj/LT-eLABa-0001:E.02~2005~D_20050614_154005-58155.
Testo completoJulien, Eric. "Alignement du chant par rapport à une référence audio en temps réel". Mémoire, Université de Sherbrooke, 2013. http://hdl.handle.net/11143/6184.
Testo completoMartins, Ana Caroline Vasconcelos. "GluA2 - Glutamatergic Receptor Study: A Molecular Approach". reponame:Repositório Institucional da UFC, 2017. http://www.repositorio.ufc.br/handle/riufc/28258.
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Glutamate receptors are the mediators of most excitatory neurotransmission processes in the central nervous system, acting as prominent targets for the treatment of several neurological disorders such as Epilepsy, Amyotrophic Lateral Sclerosis, Parkinson’s disease and Alzheimer’s disease. Hence an improved understanding of how glutamate and other ligands interact with the binding domain, of these receptors, can bring relevant insights to the development of new ligands. Therefore, this work aims to study the GluA2–ligand interaction using the structure of GluA2 co-crystallized with the ligands glutamate, AMPA, kainate and DNQX applying a method based on the Density Functional Theory combined with the molecular fractionation with conjugate caps scheme. To address that the dielectric constant of the GluA2 receptor is not homogeneous, a novel molecular approach was proposed and it was applied to study the interaction between the GluA2 and the ligands glutamate, AMPA, kainate and DNQX. The results obtained, considering the inhomogeneous model, were compared with those obtained using an uniform dielectric function for the GluA2 receptor and with data published in the literature establishing a more detailed description of the relevant amino acid residues for the protein-ligand binding interaction. Molecular dynamics studies and protein DFT calculations usually consider a fixed value for the protein dielectric function. In this work when ε = 1 is considered, many amino acid residues seem important, but when the dielectric constant shield was considered, they lost their relevance. The results for the GluA2-ligand total interaction energy and the D1-ligand and D2-ligand total interaction energy also shed some light on the differentiation between full and partial agonists, and between agonists and antagonists. Additionally, the results allow a hypothesis on the correlation between the Glu705-ligand interaction energy and the ligand action, paving the way for the use of the inhomogeneous dielectric function to study glutamate receptors and other protein-ligand systems. Finally, the results also suggests that for different ligands, different homogeneous dielectric constant will be able to well represent the system GluA2-ligand, making it necessary the previous analyses with the inhomogeneous dielectric constant approach.
Os receptores de glutamato são os mediadores da maioria dos processos de neurotransmissão excitatória no sistema nervoso central, atuando como alvos proeminentes para o tratamento de vários distúrbios neurológicos, como Epilepsia, Esclerose Lateral Amiotrófica, Doença de Parkinson e Doença de Alzheimer. Assim, uma compreensão aprimorada de como o glutamato e outros ligantes interagem com o domínio de interação, desses receptores, pode trazer informações relevantes para o desenvolvimento de novos ligantes. Portanto, este trabalho teve por objetivo estudar a interação GluA2-ligante utilizando a estrutura de GluA2 co-cristalizada com os ligantes Glutamato, AMPA, Cainato e DNQX utilizando método baseado na Teoria do Funcional da Densidade combinado com o esquema de fracionamento molecular com capas conjugadas. Para abordar que a constante dielétrica do receptor GluA2 não é homogênea, foi proposta uma nova abordagem molecular, que foi aplicada para estudar a interação entre a GluA2 e os ligantes Glutamato, AMPA, Cainato e DNQX. Os resultados obtidos, considerando o modelo não-homogêneo, foram comparados com aqueles obtidos usando uma função dielétrica uniforme para o receptor GluA2 e com dados publicados na literatura, estabelecendo uma descrição mais detalhada dos resíduos de aminoácido mais relevantes para a interação proteína-ligante. Estudos de dinâmica molecular e cálculos DFT de sistemas proteicos normalmente consideram um valor fixo para a função dielétrica proteica. Nesse trabalho quando ε = 1 é considerado, muitos resíduos de aminoácido parecem relevantes, mas quando a blindagem da constante dielétrica foi considerada, eles perderam sua relevância. Os resultados apresentados para a energia de interação total GluA2-ligante e a energia de interação total D1-ligante e D2-ligante contribuiu com a diferenciação entre agonistas totais e agonistas parciais e entre agonistas e antagonistas. Além disso, os resultados permitem que seja feita hipótese sobre a correlação entre a energia de interação Glu705-ligante e a ação do ligante, abrindo caminho para o uso da função dielétrica não-homogênea para estudar receptores de glutamato e outros sistemas proteína-ligante. Por fim, os resultados também sugerem que para diferentes ligantes, diferentes constantes dielétricas homogêneas serão capazes de representar bem o sistema GluA2-ligante, tornando necessária a análise prévia com a abordagem da constante dielétrica não-homogênea.
SILVA, HARRY ARNOLD ANACLETO. "INDEPENDENT TEXT ROBUST SPEAKER RECOGNITION IN THE PRESENCE OF NOISE USING PAC-MFCC AND SUB BAND CLASSIFIERS". PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2011. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=18212@1.
Testo completoO presente trabalho é proposto o atributo PAC-MFCC operando com Classificadores em Sub-Bandas para a tarefa de identificação de locutor independente do texto em ruído. O sistema proposto é comparado com os atributos MFCC (Coeficientes Cepestrais de Frequência Mel), PAC- MFCC (Fase Autocorrelação-MFCC ) sem uso de classificadores em sub-bandas, SSCH(Histogramas de Centróides de Sub-Bandas Espectrais) e TECC (Coeficientes Cepestrais da Energia Teager). Nesta tarefa de reconhecimento, utilizou-se a base TIMIT a qual é composta de 630 locutores onde cada um deles falam 10 frases de aproximadamente 3 segundos cada frase, das quais 8 frases foram utilizadas para treinamento e 2 para teste, obtendo-se um total de 1260 locuções para o reconhecimento. Investigou-se o desempenho dos diversos sistemas utilizando diferentes tipos de ruídos da base Noisex 92 com diferentes relação sinal ruído. Verificou-se que a taxa de acerto da técnica PAC-MFCC com classificador em Sub-Bandas apresenta o melhor desempenho em comparação com as outras técnicas quando se tem uma relação sinal ruído menor que 10dB.
In this work is proposed the use of the PAC-MFCC feature with Sub-band Classifiers for the task of text-independent speaker identification in noise. The proposed scheme is compared with the features MFCC (Mel-Frequency Cepstral Coefficients ), PAC-MFCC (Phase Autocorrelation MFCC) without subband classifiers, SSCH (Subband Spectral Centroid Histograms) and TECC (Teager Energy Cepstrum Coefficients). In this recognition task, we used the TIMIT database which consists of 630 speakers, where every one of them speak 10 utterances of 3 seconds each one approximately, of which eight utterance were used for training and two for testing, thus obtaining a total of 1260 test utterance for the recognition. We investigated the performance of these techniques using differents types of noise from the base Noisex 92 with different signal to noise ratios. It was found that the accuracy rate of the PAC-MFCC feature with Sub-band Classifiers performs better in comparison with other techniques at a lower signal noise(less than 10dB).
Libri sul tema "MFCC"
Shen ru qian chu MFC: Dissecting MFC. 2a ed. Wuhan: Hua zhong ke ji da xue chu ban she, 2001.
Cerca il testo completoMFC programming. Reading, Mass: Addison-Wesley, 1997.
Cerca il testo completoIntermediate MFC. Upper Saddle River, NJ: Prentice Hall PTR, 1998.
Cerca il testo completoCrockett, Frank. MFC Developer's workshop. Redmond, Wash: Microsoft Press, 1997.
Cerca il testo completoMFC black book. Albany, NY: Coriolis Group Books, 1998.
Cerca il testo completoE, Robichaux Paul, a cura di. Using MFC and ATL. Indianapolis, IN: QUE, 1997.
Cerca il testo completoJapan. Keizai Sangyōshō. Sangyō Gijutsu Kankyōkyoku. Kankyō Chōwa Sangyō Suishinshitsu. Materiaru furō kosuto kaikei (MFCA) dōnyū jireishū. Tōkyō: Keizai Sangyōshō Sangyō Gijutsu Kankyōkyoku Kankyō Seisakuka Kankyō Chōwa Sangyō Suishinshitsu, 2008.
Cerca il testo completoProgramming Windows 95 with MFC. Redmond, Wash: Microsoft Press, 1996.
Cerca il testo completoLearn the MFC C++ classes. Plano, Tex: Wordware Pub., 1997.
Cerca il testo completoSchildt, Herbert. MFC programming from the ground up. 2a ed. Berkeley, Calif: Osborne/McGraw-Hill, 1998.
Cerca il testo completoCapitoli di libri sul tema "MFCC"
Yan, Qin, Zhengjuan Zhou e Shan Li. "Chinese Accents Identification with Modified MFCC". In Advances in Intelligent and Soft Computing, 659–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-27334-6_77.
Testo completoLiu, Jinfeng, Tong Zhu, Xiao He e John Z. H. Zhang. "MFCC-Based Fragmentation Methods for Biomolecules". In Fragmentation, 323–48. Chichester, UK: John Wiley & Sons, Ltd, 2017. http://dx.doi.org/10.1002/9781119129271.ch11.
Testo completoGonzalez, Ruben. "Better Than MFCC Audio Classification Features". In The Era of Interactive Media, 291–301. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-3501-3_24.
Testo completoGulhane, Sushen R., D. Shirbahadurkar Suresh e S. Badhe Sanjay. "Identification of Musical Instruments Using MFCC Features". In New Trends in Computational Vision and Bio-inspired Computing, 957–68. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-41862-5_97.
Testo completoSethi, Nandini, e Dinesh Kumar Prajapati. "Text-Independent Voice Authentication System Using MFCC Features". In Advances in Intelligent Systems and Computing, 567–77. Singapore: Springer Singapore, 2020. http://dx.doi.org/10.1007/978-981-15-5113-0_45.
Testo completoSingh, Vrijendra, e Narendra Meena. "Engine Fault Diagnosis using DTW, MFCC and FFT". In Proceedings of the First International Conference on Intelligent Human Computer Interaction, 83–94. New Delhi: Springer India, 2009. http://dx.doi.org/10.1007/978-81-8489-203-1_6.
Testo completoUmarani, S. D., R. S. D. Wahidabanu e P. Raviram. "Isolated Word Recognition Using Enhanced MFCC and IIFs". In Advances in Intelligent Systems and Computing, 273–83. Berlin, Heidelberg: Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-35314-7_32.
Testo completoLi, Fuhai, Jinwen Ma e Dezhi Huang. "MFCC and SVM Based Recognition of Chinese Vowels". In Computational Intelligence and Security, 812–19. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11596981_118.
Testo completoDing, Kai, Shoujun Zheng, Xiaogang Qi, Shan Huang e Haoting Liu. "Acoustic Target Recognition Based on MFCC and SVM". In Man-Machine-Environment System Engineering, 418–23. Singapore: Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-4786-5_58.
Testo completoWang, Kai, e Kang Chen. "Classification of Heart Sounds Using MFCC and CNN". In Intelligent Computing Theories and Application, 745–56. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-84529-2_62.
Testo completoAtti di convegni sul tema "MFCC"
Bansal, Priyanka, Syed Akhtar Imam e Roma Bharti. "Speaker recognition using MFCC, shifted MFCC with vector quantization and fuzzy". In 2015 International Conference on Soft Computing Techniques and Implementations (ICSCTI). IEEE, 2015. http://dx.doi.org/10.1109/icscti.2015.7489535.
Testo completoPaseddula, Chandrasekhar, e Suryakanth V. Gangashetty. "DNN based Acoustic Scene Classification using Score Fusion of MFCC and Inverse MFCC". In 2018 IEEE 13th International Conference on Industrial and Information Systems (ICIIS). IEEE, 2018. http://dx.doi.org/10.1109/iciinfs.2018.8721379.
Testo completoNagawade, Monica S., e Varsha R. Ratnaparkhe. "Musical instrument identification using MFCC". In 2017 2nd IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT). IEEE, 2017. http://dx.doi.org/10.1109/rteict.2017.8256990.
Testo completoJhawar, Gunjan, Prajacta Nagraj e P. Mahalakshmi. "Speech disorder recognition using MFCC". In 2016 International Conference on Communication and Signal Processing (ICCSP). IEEE, 2016. http://dx.doi.org/10.1109/iccsp.2016.7754132.
Testo completoVijayan, Amritha, Bipil Mary Mathai, Karthik Valsalan, Riyanka Raji Johnson, Lani Rachel Mathew e K. Gopakumar. "Throat microphone speech recognition using mfcc". In 2017 International Conference on Networks & Advances in Computational Technologies (NetACT). IEEE, 2017. http://dx.doi.org/10.1109/netact.2017.8076802.
Testo completoWu, Yi, Qi Wang e Ruolun Liu. "Music Instrument Classification using Nontonal MFCC". In 2017 5th International Conference on Frontiers of Manufacturing Science and Measuring Technology (FMSMT 2017). Paris, France: Atlantis Press, 2017. http://dx.doi.org/10.2991/fmsmt-17.2017.88.
Testo completoChatterjee, Saikat, e W. Bastiaan Kleijn. "Auditory model based modified MFCC features". In 2010 IEEE International Conference on Acoustics, Speech and Signal Processing. IEEE, 2010. http://dx.doi.org/10.1109/icassp.2010.5495557.
Testo completoSuwannakhun, Sirimonpak, e Thaweesak Yingthawornsuk. "Characterizing Depressive Related Speech with MFCC". In 2019 14th International Joint Symposium on Artificial Intelligence and Natural Language Processing (iSAI-NLP). IEEE, 2019. http://dx.doi.org/10.1109/isai-nlp48611.2019.9045499.
Testo completoEl Badlaoui, Othmane, e Ahmed Hammouch. "Phonocardiogram classification based on MFCC extraction". In 2017 IEEE International Conference on Computational Intelligence and Virtual Environments for Measurement Systems and Applications (CIVEMSA). IEEE, 2017. http://dx.doi.org/10.1109/civemsa.2017.7995329.
Testo completoKou, Haofeng, Weijia Shang, Ian Lane e Jike Chong. "Optimized MFCC feature extraction on GPU". In ICASSP 2013 - 2013 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE, 2013. http://dx.doi.org/10.1109/icassp.2013.6639046.
Testo completoRapporti di organizzazioni sul tema "MFCC"
Jones, Robert, Molly Creagar, Michael Musty, Randall Reynolds, Scott Slone e Robyn Barbato. A 𝘬-means analysis of the voltage response of a soil-based microbial fuel cell to an injected military-relevant compound (urea). Engineer Research and Development Center (U.S.), novembre 2022. http://dx.doi.org/10.21079/11681/45940.
Testo completoRossi, Ruggero, David Jones, Jaewook Myung, Emily Zikmund, Wulin Yang, Yolanda Alvarez Gallego, Deepak Pant et al. Evaluating a multi-panel air cathode through electrochemical and biotic tests. Engineer Research and Development Center (U.S.), dicembre 2022. http://dx.doi.org/10.21079/11681/46320.
Testo completoMichael Cannon, Terry Barney, Gary Cook, Jr George Danklefsen, Paul Fairbourn, Susan Gihring e Lisa Stearns. MFC Communications Infrastructure Study. Office of Scientific and Technical Information (OSTI), gennaio 2012. http://dx.doi.org/10.2172/1035903.
Testo completoMedam, Anudeep, Michael Stadler, Abhishek Banerjee, Muhammad nmn Usman, Ning Kang, Adib Nasle, Kelsey Fahy e Zack Pecenak. Summary Report for the Microgrid Fast Charging Station (MFCS) Design Platform Project. Office of Scientific and Technical Information (OSTI), luglio 2021. http://dx.doi.org/10.2172/1813548.
Testo completoMickelsen, Zand. Project Closeout Report for the MFC Firewater Replacement Project. Office of Scientific and Technical Information (OSTI), giugno 2016. http://dx.doi.org/10.2172/1466677.
Testo completoKerry L. Nisson. Permanent Closure of MFC Biodiesel Underground Storage Tank 99ANL00013. Office of Scientific and Technical Information (OSTI), ottobre 2012. http://dx.doi.org/10.2172/1060996.
Testo completoGuan, Haiying, Andrew Delgado, Yooyoung Lee, Amy Yates, Daniel Zhou, Timothée Kheyrkhah e Jonathan G. Fiscus. User Guide for NIST Media Forensic Challenge (MFC) Datasets. National Institute of Standards and Technology, luglio 2021. http://dx.doi.org/10.6028/nist.ir.8377.
Testo completoAydogdu, Ali, Jaime Hernandez-Lasheras, Carolina Amadio, Baptiste Mourre, Gianpiero Cossarini e Jenny Pistola. Design of the glider assimilation experiments. EuroSea, 2021. http://dx.doi.org/10.3289/eurosea_d4.2.
Testo completoAydogdu, Ali. Design of the glider assimilation experiments. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d4.2_v2.
Testo completoSteele, William F. Conceptual Design Report for the Materials and Fuels Complex (MFC) Research Collaboration Building (RCB). Office of Scientific and Technical Information (OSTI), gennaio 2017. http://dx.doi.org/10.2172/1485427.
Testo completo