Unsupervised Clustering of Comments Written in Albanian Language

Unsupervised Clustering for Language Identification

The current state of the art in language identification comes from n-gram language models. While these can reach 99% accuracy (Hammarstrom, 2007), they have three major shortcomings. First, n-gram language models are supervised. They require substantial labeled training data in each language in order to be functional. For best results, this training data should also be in the same genre as the ...

Iranian EFL Learners’ Reactions to Different Feedbacks in Writing Classrooms: Teacher Written Comments (TWC) vs. Peer Written Comments (PWC)

The teaching of writing has recently begun to move away from a concentration on the written product to an emphasis on the process of writing. Feedback is a fundamental element of the process approach to writing. It can be defined as input from a reader to a writer with the effect of providing information to the writer for a revision. This study reports on the effectiveness of two types of feedb...

Application of Clustering for Unsupervised Language Learning

We describe a method for automatically learning word similarity from a corpus. We constructed feature vectors for words according to their appearance in different dependency paths in parse trees of corpus sentences. Clustering the huge amount of raw data costs too much time and memory, so we devised techniques to make the problem tractable. We used PCA to reduce the dimensionality of the featur...

‏‎interpersonal function of language in subtitling

‏‎translation as a comunicative process is always said to be associated with various aspects of meaning loss or gain. subtitling as a mode of translating, due to special discoursal and textual conditions imposed upon it, is believed to be an obvious case of this loss or gain. presenting the spoken sound track of a film in writing and synchronizing the perception of this text by the viewers with...

Appendix C Submitted Written Comments