A speech-based driver assisting module for Intelligent Transport System

Aim of this research is to transform images of roadside traffic panels to speech to assist the vehicle driver, which is a new approach in the state-of-the-art of the advanced driver assistance systems. The designed system comprises of three modules, where the first module is used to capture and detect the text area in traffic panels, second module is responsible for converting the image of the detected text area to editable text and the last module is responsible for transforming the text to speech. Additionally, during experiments, we developed a corpus of 250 images of traffic panels for two Indian languages.Comment: 3rd International Conference on Contemporary Computing and Informatics (IC3I), India, 201

Towards the Study of Morphological Processing of the Tangkhul Language

There is no or little work on natural language processing of Tangkhul language. The current work is a humble beginning of morphological processing of this language using an unsupervised approach. We use a small corpus collected from different sources of text books, short stories and articles of other topics. Based on the experiments carried out, the morpheme identification task using morphessor gives reasonable and interesting output despite using a small corpus.Comment: In proceeding of Regional International Conference on Natural Language Processing (regICON) 2017, 3rd and 4th November 2017, Imphal, Indi