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Conference papers Tamil Internet 2009 Cologne, Germany – Oct 23-25 1 2 CONTENTS Topic A. Computer Assisted Learning and Teaching of Tamil 1. E-Learning for Enhancing Language Proficiency Dr. A. Devaki and Prof. D. Mathialagan, India 2. இைணய வபைற: ெதாழி ப கேபா உளவிய (Virtual Class room: Technology and Learner's Psychology) ைனவ ெவ. கைலெசவி, இதியா 3. Preparing pedagogy for E-learning courses - A pilot plan for Tamil Nadu Dr. R. Natarajan, India 4. இைணய வழி ெமாழி கற -கபித திய அைறக ைனவ . ழைதேவ பனீெசவ, இதியா 5. Effectiveness of Multimedia Package in Learning Vocabulary in Tamil Dr. G. Singaravelu, India 6. Enhancing Learning of Tamil Language in a One-to-One Computing Environment Sivagouri Kaliamoorthy, Singapore 7. ேபதமிைழ கபிபதி கணினியி பயபா Dr. A . Ra . Sivakumaran, Singapore 8. Development of E-content for Learning Tamil Phonetics Dr. R. Velmurugan, Singapore 9. Infusing Media-Literacy to Help Learners Construct and Make Sense of their Learning Sivagouri Kaliamoorthy, Singapore 10. The Use of Technology among Tamil Medium Students – Barriers and Solutions. Prof. P. J. Paul Dhanasekaran, India 11. Learning Tamil the Fun Way Kanmani Shunmugham, Singapore 12. The Use of Multi Media in Teaching Tamil through Internet R. Subramani Topic B. Tamil Diaspora: Teaching Tamil as a Second Language and Impact of Technology: 13. தமி இைணய பகைலகழக ெசயபாக – சவாக ைனவ ப.அர. நகீர, India 14. Enhance Creativity through Multimedia: A Study in Malaysian Tamil Schools. Dr. Paramasivam Muthusamy, Malaysia 15. Use and the Impact of Information Technology in the Teacher Training Dr. Seetha Lakshmi, Singapore 16. Tamil Language teaching in UK. A case study of one supplementary school’s experience of working in partnership with a mainstream school to promote a community language. Siva Pillai, England. 17. Enhancing the Process of Learning Tamil with Synchronized Media Vasu Renganathan, U.S.A. Topic C. Tamil Portal: Blogger, Aggregator and Wikipedia 3 18. எதிகால இைணயதி தமி னிேகா: வளதமி ஆவி தரதளக , திரக ைனவ நா. கேணச, ட, அெமாிகா 19. Automatic E-Content Generation E.Iniya Nehru, India 20. ICANN and IDN Internet Corporation for Assigned Names and Numbers International Domain Names. S.Maniam, Singapore. 21. Development of Social Networking Website and Tamil E-learning Software Using Unicode / ISCII standards. Dr.A.Muthukumar, India. 22. தமி விகியா ைணதிடக : அறிக , தமி இைணயதி அவறி வகிபாக , எதிகால , ெசயைற விளக ரளிதர மர, Sri Lanka. Topic D. Tamil Localization, Tamil Keyboard and Open Source Software 23. தமி திற ெமெபாக - ‘தமிழா ’ ேதாற ெதாடசி சி.ம.இளதமி , Malaysia. 24. Indic-Keyboards – A multilingual Indic keyboard interface A.G. Ramakrishnan, Akshay Rao, Arun S., Abhinava Shivakumar, India. 25. Tamil Localisation Process – A case study Kengatharaiyer Sarveswaran, Sri Lanka. 26. தமி ெமெபாக மக பாவைன சிவா அரா – வட அெமாிகா 27. Inside Tamil Unicode Sinnathurai Srivas, Australia 28. Building Tamil Unicode Fonts for Mac OS X. Muthu Nedumaran, Malaysia 29. Tamil Encoding, Keyboard Layout and Collation Sequence Standard for ICT Sri Lanka Balachandran G. Sri Lanka Topic E. Natural Language Processing 30. An Intelligent System for Picture Based Tamil Sentence Generation Dr.T.Mala, Dr.T.V.Geetha, India 31. A HMM Based Online Tamil Word Recognizer Rituraj Kunwar, Shashi Kiran Suresh Sundaram and A G Ramakrishnan, India. 32. Problems related to Eng-Tam Translation M.B.A.Salai Aaviyamma and Dr.K.Kathiravan 33. Tamil-English Cross Lingual Information Retrieval System for Agriculture Society D. Thenmozhi and C. Aravindan Topic F. Tamil in Handheld and Mobile Phones 34. அறிவிய ம தகால ேதைவகேகற தமிெழ சீதித அவைற கணினி ம ைகேபசி ெசயபா பயப ைற த. ஞான பாரதி , India. 35. Tamil on Mobile Devices Muthu Nedumaran, Malaysia. 4 36. E=mt2 E-Learning = M-Learning makes Tamil learning Squared S. Swarnalatha, India Topic G. E-Texts, Corpora and Search Engines 37. Tamil Corpus Generation and Text Analysis M. Ganesan, India 38. OMNIS/2 Integrating Libraries with Digital Multimedia Database C.Radha, India 39. மிபதி - படக தகவ தர களசிய , ஓைலவகளி ேபரடவைண உவாக பாஷினி ெரம , ெஜமனி 40. Tamil Inscriptions and on line search: Database Compilation, Grammatical analysis, Lexicon and Translation. Appasamy Murugaiyan, France. 41. படகவழி பழதமி இலகிய கதாட இலகிய கற கபித அபைடயி (Sangam Literature Teaching and Learning through Multimedia) ைனவ வா. ேச. ராமக ஆடவ Topic H. Computational Linguistics 42. தமி விைன வவக: கணினி பபா (Computer Analysis of Tamil Verb Forms) ைனவ ப. ேடவி பிரபாக 43. Dravidian Wordnet (திராவிட ெசாவைலயாக ) Dr. S.Rajendran, India. 44. Unsupervised Approach to Tamil Morpheme Segmentation K.Rajan, Dr. V.Ramalingam, Dr. M.Ganesan, India. 45. ெதாகாபியதி எததிகாரகான இட சாரா இலகண இல. பாலதரராம, ஈவ சிாீதர Topic I. Natural Langauge Processing: Morphological Tagger 46. AMRITA Morph Analyzer and Generator for Tamil: A Rule Based Approach Dr. A.G. Menon, Amrita and Leiden (Netherland), S. Saravanan, R. Loganathan and Dr. K. Soman, India. 47. A Novel Approach to Morphological Analysis for Tamil Language (தமி உபனிய ஆவி ஒ திய அைற) Anand kumar M, Dhanalakshmi V, Rajendran S, Soman K 48. POS Tagger and Chunker for Tamil Language (தமி ெசாவைக அைடயாளபதி ம ெதாட பபா) Dhanalakshmi V, Anand kumar M, Rajendran S, Soman K 5 Topic J. Electronic Tamil Dictionaries and Glossaries 49. தகவ ெதாழிப கைலெசாகைள வளபக மா. ஆேடா ட , இதியா . 50. Electronic Dictionary for Sangam Literature (சக இலகியதிகான மி அகராதி) Dr. K.Umaraj, India 51. கணிணியிய ேநெபய ெசாக ஒெபய ெசாக இலவனா திவவ, இதியா 52. Critical Editions of Tamil Works: Exploratory Survey and Future Perspectives Jean-Luc Chevillard, France 53. The English Dictionary of the Tamil Verb: What can it tell us about the structure of Tamil? Harold F. Schiffman, U.S.A. 6 7 மேலசிய லெதாழி அைமச டேதா டாட எ.ரமணிய அவகளி வாெசதி தமி இைணய மாநா இவா ெஜமனியி நைடெபவைத எணி மகிசியைடகிேற. தமி கணினி வளசி தமி ெமாழியி வளசி இைணய மாநாக கிய பகாறி வவ அறி மகிகிேற. தமி ெமாழி வளமான ெமாழி எப அைனவ ெதாி , வளமான இெமாழிைய அத தைலைறயின ெகா ெச கவி ெதாழிபமாக கணினி இைணய திககிற . இெதாழிபைத ெகா தமிகாக சீாிய பணிக ஆறி வ தமி இைணய 2009 ஏபா வினைர மனவ வாகிேற. தமி தகவ ெதாழிபதிகான அைனலக மறமான உதம , ெஜமனியி அைமள ேகால பகைலகழகதி தமி ஆ ைமய இைண நட இமாநா எலா வைகயி சிறட நைடெபற எைடய வாக . 8 மேலசிய , டர பிரேதச ைண அைமச டேதா சரவண அவகளி வாெசதி தமி கணினி வளசி எப இ தமி ெமாழி வளசியி கிய றாக விளகி வகிற . எதிவ அேடாப 23 ெதாடகி 25 வைர ெஜமனியி நைடெபற உள தமி இைணய மாநா வா ெதாிவிபதி மடற மகிசி மகிகிேற. தமி தகவ ெதாழிபதிகான அைனலக மறமான உதம , ெஜமனியி அைமள ேகால பகைலகழகதி தமி ஆ ைமய இைண நட இமாநா எலா வைகயி ெவறி ெப எப திண . இவைர ெசைன (1997, 1999, 2003), சிைக (2000, 2004), மேலசியா (2001), அெமாிகா (2002) நைடெபள இமாநா , இவா ல ெபயத தமிழக அதிக வா ஐேராபாவி நைடெபவ தமி ெமாழியி வளசி விைரவாக விதி . 2001- ம.இ.காவி உதவிட ேகாலாலாி நைடெபற தமி இைணய மாநாைன ெபமிதட திபி பாகிேற ‘ கணினி வழி காேபா தமி ’ எ கெபாளி நைடெபறவி இமாநா தமி தகவ ெதாழிப உலகி ஏபவ சவாகைள மாறகைள ஒேக ஆரா தீவிைன ெகா வ என ெபாி எதிபாகிேற தமி இைணய 2009 சிறபாக நைடெபற சீாிய பணிக ஆறி வ ஏபா வினைர மனவ வாகிேற. 9 Prof. M. Anandakrishnan Chairman, IIT-Kanpur & Science City, Chennai, Tamilnadu Chair, INFITT 2000-2003 Cologne INFITT Conference Reflects Optimism with Realism Starting from late seventies and early eighties, the developments in personal computers provoked a number of Tamil professionals to undertake significant efforts to achieve incorporation of Tamil language in computers and the fledgling internet. Most of them like Srinivasan, from Quebec, Canada and Kalyanasundaram from Lausanne, Swizerland and many others like them were not formally trained computer professionals. Some like Muthu Nedumaran from Kuala Lumpur, Malaysia were computer experts with accomplishments in language computing. There were many others like them in France, Germany, USA, Canada, Australia, Singapore, Malaysia, Sri Lanka and India. Their initial contributions were mostly boot-strapping part-time efforts out of genuine enthusiasm but had very little scope for exchange of ideas. By late eighties, the degree of incompatibility among these efforts rendered the value of their contributions mainly local and limited. They did not subscribe to the prevailing international standards either because of their not being aware of them or due to serious disagreement with them.
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    AGNALDO DA COSTA TAXONOMIA PARA FERRAMENTAS DE AUTORIA: APOIO NA ELABORAÇÃO DE MATERIAIS DIDÁTICOS DIGITAIS Itajaí (SC), Dezembro de 2012 UNIVERSIDADE DO VALE DO ITAJAÍ CURSO DE MESTRADO ACADÊMICO EM COMPUTAÇÃO APLICADA TAXONOMIA PARA FERRAMENTAS DE AUTORIA: APOIO NA ELABORAÇÃO DE MATERIAIS DIDÁTICOS DIGITAIS por Agnaldo da Costa Dissertação apresentada como requisito parcial à obtenção do grau de Mestre em Computação Aplicada. Orientador: André L. A. Raabe, Doutor Itajaí (SC), dezembro de 2012 A nossa maior glória não reside no fato de nunca cairmos, mas sim em levantarmo-nos sempre depois de cada queda (Confúcio) AGRADECIMENTOS Uma dissertação de mestrado não é tarefa fácil, ainda mais se tratando de pesquisa na área da Computação onde o avanço da tecnologia se faz de forma bastante dinâmica. Para superar esse desafio contei com o apoio de diversas pessoas as quais gostaria de agradecer porque estiveram ao meu lado na construção desse desafio. Primeiramente quero agradecer a Deus, pela saúde, disposição, e por ter me dado motivação para não desistir quando eu mesmo nem acreditava mais em mim. A minha noiva Sheila Manske por aguentar tantas reclamações e sempre me motivar para que pudesse terminar e realizar o meu sonho em ser mestre na área de computação. Ao meu orientador André A. Raabe, por ter acreditado no meu potencial e apostar em um projeto na fase inicial (do zero, mesmo!) e quando eu não tinha mais para onde ir. Por vibrar em cada conquista e por me apoiar apesar das fraquezas. Esse é um exemplo que deve ser seguido por outros educadores. Aos meus familiares: pai, mãe, irmãos, por torcerem por mim.
  • Print This Article

    Print This Article

    European Journal of Foreign Language Teaching ISSN: 2537 - 1754 ISSN-L: 2537 - 1754 Available on-line at: www.oapub.org/edu doi: 10.46827/ejfl.v5i4.3688 Volume 5 │ Issue 4 │ 2021 A NEW APPROACH FOR DISTANCE LANGUAGE LEARNING: COMPARING CURRENT PROGRAMS AND EFFECTIVENESS OF AUDIO EDITING PROGRAMS Aysel Deregözü1i, Volkan Kanburoğlu2 1Inonu University, Malatya, Turkey 2Marmara University, Istanbul, Turkey Abstract: The main goal in language education is to develop learners’ skills in oral communication that enables to interact in the target language. Yet, in times of the pandemic, activities supporting the development of communicative competences are difficult to implement, as these activities are arranged mostly for in – class settings with the need of students’ interactive participation. Hence, language education needs to be adapted according to the new circumstances. The aim of this study is to examine how open source audio editing programs can support language education especially in promoting oral competences and implementing communicative activities for in – class language education with social distance and distanced language education. For this aim, open source audio editing programs are examined and compared in view of their features. Within this aim the programs Audacity, Ardour, Ecasound, Jokosher, MusE, Qtractor, Rosegarden, SoX, Sweep and Traverso DAW are examined. Furthermore, on the example of the program Audacity, some useful features for preparing audios in language education are presented. It is recommended to use these programs in language education. Keywords: communicative competence, language education, distance learning, audio editing program, technology 1. Introduction Learning a language means to acquire skills, that enable their users to communicate in the target language.
  • Free and Open Source Software

    Free and Open Source Software

    Free and open source software Copyleft ·Events and Awards ·Free software ·Free Software Definition ·Gratis versus General Libre ·List of free and open source software packages ·Open-source software Operating system AROS ·BSD ·Darwin ·FreeDOS ·GNU ·Haiku ·Inferno ·Linux ·Mach ·MINIX ·OpenSolaris ·Sym families bian ·Plan 9 ·ReactOS Eclipse ·Free Development Pascal ·GCC ·Java ·LLVM ·Lua ·NetBeans ·Open64 ·Perl ·PHP ·Python ·ROSE ·Ruby ·Tcl History GNU ·Haiku ·Linux ·Mozilla (Application Suite ·Firefox ·Thunderbird ) Apache Software Foundation ·Blender Foundation ·Eclipse Foundation ·freedesktop.org ·Free Software Foundation (Europe ·India ·Latin America ) ·FSMI ·GNOME Foundation ·GNU Project ·Google Code ·KDE e.V. ·Linux Organizations Foundation ·Mozilla Foundation ·Open Source Geospatial Foundation ·Open Source Initiative ·SourceForge ·Symbian Foundation ·Xiph.Org Foundation ·XMPP Standards Foundation ·X.Org Foundation Apache ·Artistic ·BSD ·GNU GPL ·GNU LGPL ·ISC ·MIT ·MPL ·Ms-PL/RL ·zlib ·FSF approved Licences licenses License standards Open Source Definition ·The Free Software Definition ·Debian Free Software Guidelines Binary blob ·Digital rights management ·Graphics hardware compatibility ·License proliferation ·Mozilla software rebranding ·Proprietary software ·SCO-Linux Challenges controversies ·Security ·Software patents ·Hardware restrictions ·Trusted Computing ·Viral license Alternative terms ·Community ·Linux distribution ·Forking ·Movement ·Microsoft Open Other topics Specification Promise ·Revolution OS ·Comparison with closed
  • Linux-Sound-Book.Txt.Pdf

    Linux-Sound-Book.Txt.Pdf

    Linux Audio \" Contents 1 Beeping And Synthesizing1 12 Adding Sound Effects6 2 Curiosities2 13 Using The Sox Tool6 3 Sound Settings2 14 Fidelity Or Sound Quality7 4 Jukeboxes2 15 Sound Volume7 5 Internet Radio2 16 Extracting Audio From Video8 6 Playing Sound Files2 17 Splitting Sound Files9 7 Editing Sound Files3 18 Play Lists9 8 Finding Sound Files3 19 Synth Music9 9 Recording Sound3 20 Metadata9 10 Audio Cds4 21 Speech Synthesis9 10.1 Playing Audio Compact Disks...... 4 22 Internet Phone Calls9 10.2 Copying Cd Audio ............ 4 23 Curiosities9 10.3 Burning Compact Discs ......... 5 24 Notes9 11 Converting Sound Formats5 . This book tries to contain succint recipes for using audio files with the linux operating system, with a special emphasis on using the command line (bash shell). waon: converts waves to notes timidity: converts notes to waves To select a device for recording, use set followed by the name of the sound jargon gain Like the volume channels Whether sound is mono, stereo or surround sound herz The number of samples per second samples midi Synthesized music or sound Unencrypted voicechat [On PC1] nc -l -p 6666 > /dev/dsp [On PC2] cat /dev/dsp | nc <PC1's IP> 6666 Keep from having to adjust your volume constantly find . -iname \*.mp3 -print0 | xargs -0 mp3gain -krd 6 && vorbisgain - ) rfs . Tune your guitar from the command line. for n in E2 A2 D3 G3 B3 E4;do play -n synth 4 pluck $n repeat 2;done 1 Section 1 Beeping And Synthesizing Ring the bell alias beep='echo -en "\007"' MP3 SOUND FILES Reduce mp3 bit-rate (and size, of course) lame --mp3input -m m --resample 24 input.mp3 Play the mp3 sound file 'test.mp3' mpg123 test.mp3 mpg321 test.mp3 ~ (more efficient where no floating-point unit) Play the MP3 stream at the url mpg321 http://example.net/broadcast/live.mp3 When not recording sound, keep the inputs muted Change the sampling rate of 'old.wav' to 7,000 Hz, and write to 'new.wav' sox old.wav -r 7000 new.wav This command writes a new file, 'new.cdr', in the audio CD format; the original file, 'new.wav', is not altered.