المؤلفون: Tay, Ahmad, Andries, Mihai, Lohr, Christophe

المساهمون: Contrôle et Diagnostic pour l’Environnement (CDE), Laboratoire d'Informatique et des Systèmes (LIS) (Marseille, Toulon) (LIS), Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS)-Aix Marseille Université (AMU)-Université de Toulon (UTLN)-Centre National de la Recherche Scientifique (CNRS), Département Informatique (IMT Atlantique - INFO), IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT), Equipe Robot interaction, Ambient system, Machine learning, Behaviour, Optimization (Lab-STICC_RAMBO), Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC), École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique), Institut Mines-Télécom Paris (IMT), Mementop project: cofunded by the French Agence Nationale de la Recherche (ANR) through the Plan "France Relance" and the Smart Macadam company., Mementop

المصدر: https://hal.science/hal-04612243Test ; 2024.

مصطلحات موضوعية: Dementia, Dementia disease, artificial neural networks, class-dependent principal component analysis, speech analysis, classification, [SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing

العلاقة: hal-04612243; https://hal.science/hal-04612243Test; https://hal.science/hal-04612243/documentTest; https://hal.science/hal-04612243/file/2024.05.07d%20Article_EAAI__Dementia_detection_based_on_speech_acoustics_using_machine_learning.pdfTest

الإتاحة: https://hal.science/hal-04612243Test
https://hal.science/hal-04612243/documentTest
https://hal.science/hal-04612243/file/2024.05.07d%20Article_EAAI__Dementia_detection_based_on_speech_acoustics_using_machine_learning.pdfTest

المؤلفون: Pérez-Toro, PA, Dineley, J, Kaczkowska, A, Conde, P, Zhang, Y, Matcham, F, Siddi, S, Haro, JM, Bruce, S, Wykes, T, Bailón, R, Vairavan, S, Dobson, RJB, Maier, A, Nöth, E, Orozco-Arroyave, JR, Narayan, VA, Hotopf, M, Cummins, N

المصدر: In: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). (pp. pp. 12021-12025). IEEE: Seoul, Korea, Republic of. (2024)

مصطلحات موضوعية: Training, Adaptation models, Speech analysis, Sociology, Mental health, Signal processing, Depression

وصف الملف: application/pdf

العلاقة: https://discovery.ucl.ac.uk/id/eprint/10193575/1/Longitudinal%20modeling%20of%20depression%20shifts%20using%20speech%20and%20language.pdfTest; https://discovery.ucl.ac.uk/id/eprint/10193575Test/

الإتاحة: https://discovery.ucl.ac.uk/id/eprint/10193575/1/Longitudinal%20modeling%20of%20depression%20shifts%20using%20speech%20and%20language.pdfTest
https://discovery.ucl.ac.uk/id/eprint/10193575Test/

المؤلفون: MA'AYAH, Husam

المساهمون: Université de Brest (UBO), Héritages et Constructions dans le Texte et l'Image (HCTI), Université de Bretagne Sud (UBS)-Université de Brest (UBO)-Institut Brestois des Sciences de l'Homme et de la Société (IBSHS)

المصدر: https://hal.science/hal-04106943Test ; 2023.

مصطلحات موضوعية: Linguistic speech, Speech analysis, Political communication, Political speech, Discours politique, Discours linguistique, L'analyse du discours, La communication politique, [SCCO.LING]Cognitive science/Linguistics

العلاقة: hal-04106943; https://hal.science/hal-04106943Test; https://hal.science/hal-04106943/documentTest; https://hal.science/hal-04106943/file/ANALYSE%20DU%20DISCOURS%20LINGUISTICO-POLITIQUE%20%20DE%20L%E2%80%99HISTOIRE%20AU%20PR%C3%89SENT.pdfTest

الإتاحة: https://hal.science/hal-04106943Test
https://hal.science/hal-04106943/documentTest
https://hal.science/hal-04106943/file/ANALYSE%20DU%20DISCOURS%20LINGUISTICO-POLITIQUE%20%20DE%20L%E2%80%99HISTOIRE%20AU%20PR%C3%89SENT.pdfTest

المؤلفون: Marian Elaine De Chavez (11923370)

مصطلحات موضوعية: Linguistics, Applied Linguistics and Educational Linguistics, computational linguistics, speech analysis, analytical

العلاقة: https://figshare.com/articles/preprint/Personal_Pronoun_Analysis_on_Abraham_Lincoln_s_Selected_Speeches_Could_Indicate_Effectiveness_of_Speech_Writing/18093854Test

الإتاحة: https://doi.org/10.6084/m9.figshare.18093854.v1Test

المؤلفون: Flórez-Gómez, Andrés Felipe, Orozco-Arroyave, Juan Rafael, Roldán-Vasco, Sebastián

المصدر: TecnoLógicas; Vol. 25 No. 53 (2022); e2220 ; TecnoLógicas; Vol. 25 Núm. 53 (2022); e2220 ; 2256-5337 ; 0123-7799

مصطلحات موضوعية: Dysphagia, Speech analysis, Voice analysis, Biosignal processing, Feature extraction, Statistical analysis, Disfagia, análisis de voz, análisis del habla, procesamiento de bioseñales, extracción de características, análisis estadístico

وصف الملف: application/pdf; application/zip; text/xml; text/html

العلاقة: https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2220/2353Test; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2220/2354Test; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2220/2355Test; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2220/2356Test; L. Sura; A. Madhavan; G. Carnaby; M. Crary, “Dysphagia in the elderly: management and nutritional considerations”, Clin. Interv. Aging, vol. 2012, no. 7, pp. 287-298, Jul. 2012. https://doi.org/10.2147/CIA.S23404Test; D. C. Wolf, “Dysphagia”, en Clinical Methods: The History, Physical, and Laboratory Examinations, 3a ed., Eds. Boston: Butterworths, 1990. https://www.ncbi.nlm.nih.gov/books/NBK408Test/; A. Farri; A. Accornero; C. Burdese, “Social importance of dysphagia: its impact on diagnosis and therapy”, Acta Otorhinolaryngol Ital, vol. 27, no. 2, pp. 83–6, Abr. 2007. http://www.ncbi.nlm.nih.gov/pubmed/17608136Test; O. Ortega; A. Martín; P. Clavé, “Diagnosis and Management of Oropharyngeal Dysphagia Among Older Persons, State of the Art”, J. Am. Med. Dir. Assoc., vol. 18, no. 7, pp. 576–582, Jul. 2017. https://doi.org/10.1016/j.jamda.2017.02.015Test; Ministerio de Salud y Protección Social Oficina de Promoción Social, “Sala situacional de la Población Adulta Mayor”, Minist. Salud y Protección Soc., pp. 1-8, 2018. https://www.minsalud.gov.co/sites/rid/Lists/BibliotecaDigital/RIDE/DE/PS/sala-situacion-envejecimiento-2018.pdfTest; S. E. Langmore, “Evaluation of oropharyngeal dysphagia: which diagnostic tool is superior?”, Curr. Opin. Otolaryngol. Head Neck Surg., vol. 11, no. 6, pp. 485–489, Dic. 2003. http://journals.lww.com/00020840-200312000-00014Test; T. Warnecke et al., “The Safety of Fiberoptic Endoscopic Evaluation of Swallowing in Acute Stroke Patients”, Stroke, vol. 40, no. 2, pp. 482–486, Feb. 2009. https://doi.org/10.1161/STROKEAHA.108.520775Test; S. Restrepo-Agudelo; S. Roldan-Vasco; L. Ramirez-Arbelaez; S. Cadavid-Arboleda; E. Perez-Giraldo; A. Orozco-Duque, “Improving surface EMG burst detection in infrahyoid muscles during swallowing using digital filters and discrete wavelet analysis”, J. Electromyogr. Kinesiol., vol. 35, pp. 1–8, Aug. 2017. https://doi.org/10.1016/j.jelekin.2017.05.001Test; C. M. Steele et al., “Development of a Non-invasive Device for Swallow Screening in Patients at Risk of Oropharyngeal Dysphagia: Results from a Prospective Exploratory Study”, Dysphagia, vol. 34, no. 5, pp. 698–707, Oct. 2019. https://doi.org/10.1007/s00455-018-09974-5Test; D. H. McFarland; P. Tremblay, “Clinical implications of cross-system interactions”, Semin. Speech Lang., vol. 27, no. 4, pp. 300–310, 2006. https://doi.org/10.1055/s-2006-955119Test; D. Farneti, “Voice and Dysphagia”, en Dysphagia: Diagnosis and Treatment, O. Ekberg, Ed. Cham: Springer International Publishing, 2017, pp. 257–274. https://doi.org/10.1007/174_2017_110Test; A. E. Aronson, Clinical voice disorders. Thieme Inc., 1990.; T. Warms; J. Richards, “``Wet Voice’’ as a Predictor of Penetration and Aspiration in Oropharyngeal Dysphagia”, Dysphagia, vol. 15, no. 2, pp. 84–88, Mar. 2000. https://doi.org/10.1007/s004550010005Test; S. Murugappan; S. Boyce; S. Khosla; L. Kelchner; E. Gutmark, “Acoustic characteristics of phonation in ‘wet voice’ conditions”, J. Acoust. Soc. Am., vol. 127, no. 4, pp. 2578–2589, Abr. 2010. https://doi.org/10.1121/1.3308478Test; M. E. Dajer; P. R. Scalassara; J. L. Marrara; J. C. Pereira, “Voice analysis of patients with neurological disorders using acoustical and nonlinear tools”, IEEE Int. Work. Mach. Learn. Signal Process. MLSP, 2012. http://dx.doi.org/10.1109/mlsp.2012.6349803Test; K. López-De-Ipiña et al., “Advances in a multimodal approach for dysphagia analysis based on automatic voice analysis”, en Smart Innovation, Systems and Technologies, 2016, vol. 54, pp. 201–211. https://doi.org/10.1007/978-3-319-33747-0_20Test; J. S. Ryu; S. R. Park; K. H. Choi, “Prediction of laryngeal aspiration using voice analysis”, Am. J. Phys. Med. Rehabil., vol. 83, no. 10, pp. 753–757, Oct. 2004. http://dx.doi.org/10.1097/01.PHM.0000140798.97706.A5Test; K. W. Dos Santos; B. Scheeren; A. C. Maciel; M. Cassol, “Vocal variability post swallowing in individuals with and without oropharyngeal dysphagia”, Int. Arch. Otorhinolaryngol., vol. 19, no. 1, pp. 61–66, 2015. https://doi.org/10.1055/s-0034-1394129Test; J. R. Orozco-Arroyave et al., “NeuroSpeech: An open-source software for Parkinson’s speech analysis”, Digit. Signal Process. A Rev. J., vol. 77, pp. 207–221, Jun. 2018. https://doi.org/10.1016/j.dsp.2017.07.004Test; J. R. Orozco-Arroyave; J. D. Arias-Londoño; J. F. Vargas-Bonilla; M. C. González-Rátiva; E. Nöth, “New Spanish speech corpus database for the analysis of people suffering from Parkinson’s disease”, Proc. 9th Int. Conf. Lang. Resour. Eval. Lr. 2014, pp. 342–347, 2014. http://www.lrec-conf.org/proceedings/lrec2014/pdf/7_Paper.pdfTest; Y. Jadoul; B. Thompson; B. de Boer, “Introducing Parselmouth: A Python interface to Praat”, J. Phon., vol. 71, pp. 1–15, Nov. 2018. https://doi.org/10.1016/j.wocn.2018.07.001Test; P. Boersma; D. Weenink, “Praat: doing phonetics by computer [Computer program]”. 2001, [En línea]. Disponible en: http://www.praat.orgTest/; J. C. Catford; J. H. Esling, “Phonetics, Articulatory”, en Encyclopedia of Language & Linguistics, Elsevier, 2006, pp. 425–442. https://doi.org/10.1016/B0-08-044854-2/00002-XTest; F. R. Bach; M. I. Jordan, “Discriminative Training of Hidden Markov Models for Multiple Pitch Tracking [speech processing examples]”, en Proceedings. (ICASSP ’05). IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), Philadelphia, 2005, vol. 5, pp. 489–492. http://doi.org/10.1109/ICASSP.2005.1416347Test; P. Boersma, “Acurate short-term analysis of the fundamental frequency and the harmonics-to-noise ratio of a sampled sound”, IFA Proc. 17, pp. 97–110, 1993. https://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.218.4956&rep=rep1&type=pdfTest; S. Strömbergsson, “Today’s most frequently used F0 estimation methods, and their accuracy in estimating male and female pitch in clean speech”, Proc. Annu. Conf. Int. Speech Commun. Assoc. INTERSPEECH, pp. 525–529, Sep. 2016. http://dx.doi.org/10.21437/Interspeech.2016-240Test; S. Basu; J. Chakraborty; M. Aftabuddin, “Emotion Recognition from Speech using Convolutional Neural Network with Recurrent Neural Network Architecture”, en 2nd International Conference on Communication and Electronics Systems (ICCES), Coimbatore 2017, pp. 333–336. https://doi.org/10.1109/CESYS.2017.8321292Test; A. Shukla; R. Tiwari; R. Kala, “Speech Signal Analysis”, en Studies in Computational Intelligence, vol. 307, Springer, Berlin, Heidelberg, 2010, pp. 111–128. https://doi.org/10.1007/978-3-642-14344-1_5Test; S. Skodda; W. Visser; U. Schlegel, “Vowel articulation in parkinson’s disease”, J. Voice, vol. 25, no. 4, pp. 467–472, Jul. 2011. https://doi.org/10.1016/j.jvoice.2010.01.009Test; G. Fant, Acoustic theory of speech production. The Hague: Mouton, 1960.; K. N. Stevens; A. S. House, “Development of a Quantitative Description of Vowel Articulation”, J. Acoust. Soc. Am., vol. 27, no. 3, pp. 484–493, May. 1955. https://doi.org/10.1121/1.1907943Test; M. Blomgren; M. Robb; Y. Chen, “A note on vowel centralization in stuttering and nonstuttering individuals”, J. Speech, Lang. Hear. Res., vol. 41, no. 5, pp. 1042–1051, Oct. 1998. https://doi.org/10.1044/jslhr.4105.1042Test; M. Guzmán, “Acústica Del Tracto Vocal”, 2010. https://www.logopediapsicologia.com/wp-content/uploads/acustica-del-tracto-vocal.pdfTest; S. Davis; P. Mermelstein, “Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences”, IEEE Trans. Acoust., vol. 28, no. 4, pp. 357–366, Ago. 1980. https://doi.org/10.1109/TASSP.1980.1163420Test; L. Moro-Velázquez; J. A. Gómez-García; J. I. Godino-Llorente; J. Villalba; J. R. Orozco-Arroyave; N. Dehak, “Analysis of speaker recognition methodologies and the influence of kinetic changes to automatically detect Parkinson’s Disease”, Appl. Soft Comput., vol. 62, pp. 649–666, Jan. 2018. https://doi.org/10.1016/j.asoc.2017.11.001Test; F. O. López-pabón; T. Arias-vergara; J. R. Orozco-Arroyave, “Cepstral Analysis and Hilbert- Huang Transform for Automatic Detection of Parkinson ’ s Disease”, TecnoLógicas, vol. 23, no. 47, pp. 93–108, Jan. 2020. https://doi.org/10.22430/22565337.1401Test; B. B. Monson; E. J. Hunter; A. J. Lotto; B. H. Story, “The perceptual significance of high-frequency energy in the human voice”, Front. Psychol., vol. 5, no. 587, pp. 1–11, Jun. 2014. https://doi.org/10.3389/fpsyg.2014.00587Test; E. Zwicker, “Subdivision of the Audible Frequency Range into Critical Bands (Frequenzgruppen)”, J. Acoust. Soc. Am., vol. 33, no. 2, pp. 248, feb. 1961. https://doi.org/10.1121/1.1908630Test; E. Zwicker; E. Terhardt, “Analytical expressions for critical‐band rate and critical bandwidth as a function of frequency”, J. Acoust. Soc. Am., vol. 68, no. 5, pp. 1523–1525, Aug. 1998. https://doi.org/10.1121/1.385079Test; J. R. Orozco-Arroyave et al., “Automatic detection of Parkinson’s disease in running speech spoken in three different languages”, J. Acoust. Soc. Am., vol. 139, no. 1, pp. 481-500, Jan. 2016. https://doi.org/10.1121/1.4939739Test; P. Maragos; T. F. Quatieri; J. F. Kaiser, “Speech nonlinearities, modulations, and energy operators”, in [Proceedings] ICASSP 91: 1991 International Conference on Acoustics, Speech, and Signal Processing, Toronto, 1991. https://doi.org/10.1109/ICASSP.1991.150366Test; R. B. Randall; W. A. Smith, “Application of the Teager Kaiser Energy Operator to Machine Diagnostics”, en Conference: Tenth DST Group International Conference on Health and Usage Monitoring Systems (HUMS), Melbourne, 2017, pp. 26–28. https://www.researchgate.net/publication/316284738Test; M. Tatham; K. Morton, “Speech Production: Prosody”, en Speech Production and Perception, London: Palgrave Macmillan UK, 2006, pp. 121–163. https://doi.org/10.1057/9780230513969_5Test; S. Roldan-Vasco; A. Orozco-Duque; J. C. Suarez-Escudero; J. R. Orozco-Arroyave , “Machine learning based analysis of speech dimensions in functional oropharyngeal dysphagia”, Comput. Methods Programs Biomed., vol. 208, p. 106248, Sep. 2021. https://doi.org/10.1016/j.cmpb.2021.106248Test; K. López-de-Ipiña et al., “Automatic voice analysis for dysphagia detection”, Speech, Lang. Hear., vol. 21, no. 2, pp. 86–89, 2018. https://doi.org/10.1080/2050571X.2017.1369017Test; J. R. Orozco-Arroyave; N. García; J. F. Vargas-Bonilla; E. Nöth, “Automatic Detection of Parkinson’s Disease from Compressed Speech Recordings”, en Text, Speech, and Dialogue. TSD 2015. Lecture Notes in Computer Science, Springer, Cham, 2015, pp. 88–95. http://dx.doi.org/10.1007/978-3-319-24033-6_10Test; https://revistas.itm.edu.co/index.php/tecnologicas/article/view/2220Test

الإتاحة: https://doi.org/10.2147/CIA.S23404Test
https://doi.org/10.1016/j.jamda.2017.02.015Test
https://doi.org/10.1161/STROKEAHA.108.520775Test
https://doi.org/10.1016/j.jelekin.2017.05.001Test
https://doi.org/10.1007/s00455-018-09974-5Test
https://doi.org/10.1055/s-2006-955119Test
https://doi.org/10.1007/174_2017_110Test
https://doi.org/10.1007/s004550010005Test
https://doi.org/10.1121/1.3308478Test
https://doi.org/10.1109/mlsp.2012.6349803Test

المؤلفون: Li, Xingfeng, Shi, Xiaohan, Hu, Desheng, Li, Yongwei, Zhang, Qingchen, Wang, Zhengxia, Unoki, Masashi, Akagi, Masato

مصطلحات موضوعية: Affective computing, speech emotion recognition, acoustic representation, music theory and speech analysis, PERCEPTION, EXPRESSION, PATTERNS, FEATURES, PITCH, PERSPECTIVE, MODALITIES, KNOWLEDGE, INTERVALS, COGNITION, Acoustics, Engineering, Electrical & Electronic

العلاقة: IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING; http://ir.ia.ac.cn/handle/173211/53767Test

الإتاحة: https://doi.org/10.1109/TASLP.2023.3289312Test
http://ir.ia.ac.cn/handle/173211/53767Test

المؤلفون: Pérez, Sara Isabel, Ayma, Ana

المساهمون: Albornoz, Constanza, Aparicio, Graciela, Dagatti, Mariano, Kejner, Emilse, Mogaburo, Yanel, Moragás, Florencia, Orlando, Mariano, Santinelli, Ramiro, Torres, Germán, Ursino, Antonella

مصطلحات موضوعية: Análisis del discurso, Género, Identidad de género, Desigualdad social, Exclusión social, Neoliberalismo, Argentina, Speech analysis, Gender, Gender identity, Social inequality, Social exclusion, Neoliberalism, Argentine, Análise do discurso, Gênero, Identidade de género, Desigualdade social, Exclusão social

وصف الملف: application/pdf

العلاقة: info:eu-repo/grantAgreement/UNQ/PUNQ I+D/2019-1324/AR. Buenos Aires/Discursos, desigualdades y género en tiempos de neoliberalismo y precarización. Las reacciones neoconservadoras frente a las luchas emancipatorias en la esfera pública en Argentina; http://ridaa.unq.edu.ar/handle/20.500.11807/2927Test

الإتاحة: https://doi.org/20.500.11807/2927Test
http://ridaa.unq.edu.ar/handle/20.500.11807/2927Test
https://hdl.handle.net/20.500.11807/2927Test

المؤلفون: Ardaillon, Luc, Roebel, Axel

المساهمون: Analyse et synthèse sonores Paris, Sciences et Technologies de la Musique et du Son (STMS), Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche et Coordination Acoustique/Musique (IRCAM)-Sorbonne Université (SU)-Centre National de la Recherche Scientifique (CNRS)

المصدر: https://hal.science/hal-02438881Test ; 2019.

مصطلحات موضوعية: speech analysis, CNN, GCI detection, epoch extraction, [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing, [INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG], [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]

العلاقة: info:eu-repo/semantics/altIdentifier/arxiv/1910.10235; hal-02438881; https://hal.science/hal-02438881Test; https://hal.science/hal-02438881/documentTest; https://hal.science/hal-02438881/file/1910.10235.pdfTest; ARXIV: 1910.10235

الإتاحة: https://hal.science/hal-02438881Test
https://hal.science/hal-02438881/documentTest
https://hal.science/hal-02438881/file/1910.10235.pdfTest

المؤلفون: Palacios Palacios, Sandra

مصطلحات موضوعية: SEMÁNTICA, ESPAÑOL, ANÁLISIS DEL DISCURSO, AMÉRICA LATINA, SEMANTIC, SPANISH, SPEECH ANALYSIS, LATIN AMERICA

وصف الملف: application/pdf

العلاقة: http://hdl.handle.net/11056/14624Test

الإتاحة: http://hdl.handle.net/11056/14624Test

المؤلفون: KATAYAMA , Mika, HOSHIKAWA, Tomomi

المصدر: 岡山大学教師教育開発センター紀要

مصطلحات موضوعية: ５歳児 (5-year-old children), 発話分析 (speech analysis), 振り返りの時間 (class conversations), 話し合い活動 (reflection time), 保育者 (preschool teacher)

العلاقة: https://ousar.lib.okayama-u.ac.jp/files/public/6/61568/20210325113514619543/cted_011_101_115.pdfTest; https://ousar.lib.okayama-u.ac.jp/61568Test

الإتاحة: https://doi.org/10.18926/CTED/61568Test
https://ousar.lib.okayama-u.ac.jp/files/public/6/61568/20210325113514619543/cted_011_101_115.pdfTest
https://ousar.lib.okayama-u.ac.jp/61568Test