In this paper,Modified Multi-scale Segmentation Network(MMU-SNet)method is proposed for Tamil text recognition.Handwritten texts from digi-tal writing pad notes are used for text recognition.Handwritten words recognit...In this paper,Modified Multi-scale Segmentation Network(MMU-SNet)method is proposed for Tamil text recognition.Handwritten texts from digi-tal writing pad notes are used for text recognition.Handwritten words recognition for texts written from digital writing pad through text file conversion are challen-ging due to stylus pressure,writing on glass frictionless surfaces,and being less skilled in short writing,alphabet size,style,carved symbols,and orientation angle variations.Stylus pressure on the pad changes the words in the Tamil language alphabet because the Tamil alphabets have a smaller number of lines,angles,curves,and bends.The small change in dots,curves,and bends in the Tamil alphabet leads to error in recognition and changes the meaning of the words because of wrong alphabet conversion.However,handwritten English word recognition and conversion of text files from a digital writing pad are performed through various algorithms such as Support Vector Machine(SVM),Kohonen Neural Network(KNN),and Convolutional Neural Network(CNN)for offline and online alphabet recognition.The proposed algorithms are compared with above algorithms for Tamil word recognition.The proposed MMU-SNet method has achieved good accuracy in predicting text,about 96.8%compared to other traditional CNN algorithms.展开更多
Multimodal as digital literacies are,they have still been text-based.It has been a great concern that due to the popularity of speech-like writing style online,digital literacies have brought informal speech expressio...Multimodal as digital literacies are,they have still been text-based.It has been a great concern that due to the popularity of speech-like writing style online,digital literacies have brought informal speech expressions into formal standard writing,and thus increasing the possibility to ruin the standard writing language.On the other hand,although there are moral panics of the survival of standard written languages,scholars and popular media show great tolerance for online languages.In addition,it has been proved that some frequent participants in digital literacies nowadays are capable of both online language and standard offline language,indicating that they are well aware of the different registers of language use and therefore of high language literacy.Furthermore,researches suggest several possible merits of digital literacies,including saving young people from social isolation and depression,providing people with more opportunities to learn new things and to practice the instructional writing,calling for thorough consideration and elaborate editing and encouraging brief and clear writing style.展开更多
文摘In this paper,Modified Multi-scale Segmentation Network(MMU-SNet)method is proposed for Tamil text recognition.Handwritten texts from digi-tal writing pad notes are used for text recognition.Handwritten words recognition for texts written from digital writing pad through text file conversion are challen-ging due to stylus pressure,writing on glass frictionless surfaces,and being less skilled in short writing,alphabet size,style,carved symbols,and orientation angle variations.Stylus pressure on the pad changes the words in the Tamil language alphabet because the Tamil alphabets have a smaller number of lines,angles,curves,and bends.The small change in dots,curves,and bends in the Tamil alphabet leads to error in recognition and changes the meaning of the words because of wrong alphabet conversion.However,handwritten English word recognition and conversion of text files from a digital writing pad are performed through various algorithms such as Support Vector Machine(SVM),Kohonen Neural Network(KNN),and Convolutional Neural Network(CNN)for offline and online alphabet recognition.The proposed algorithms are compared with above algorithms for Tamil word recognition.The proposed MMU-SNet method has achieved good accuracy in predicting text,about 96.8%compared to other traditional CNN algorithms.
文摘Multimodal as digital literacies are,they have still been text-based.It has been a great concern that due to the popularity of speech-like writing style online,digital literacies have brought informal speech expressions into formal standard writing,and thus increasing the possibility to ruin the standard writing language.On the other hand,although there are moral panics of the survival of standard written languages,scholars and popular media show great tolerance for online languages.In addition,it has been proved that some frequent participants in digital literacies nowadays are capable of both online language and standard offline language,indicating that they are well aware of the different registers of language use and therefore of high language literacy.Furthermore,researches suggest several possible merits of digital literacies,including saving young people from social isolation and depression,providing people with more opportunities to learn new things and to practice the instructional writing,calling for thorough consideration and elaborate editing and encouraging brief and clear writing style.
