Confusion network decoding has been very successful in combining speech-to-text (STT) outputs (Fiscus 1997; Evermann and Woodland, 2000; Mangu et al., 2000) from diverse systems using different modeling assumptions. Several modeling paradigms have been introduced in machine translation (MT) including rule-based, phrase-based, hierarchical, syntax-based and even cascades of rule-based and statis...

Words that participate in the sentiment (positive or negative) classification decision are known as significant words for sentiment classification. Identification of such significant words as features from the corpus reduces the amount of irrelevant information in the feature set under supervised sentiment classification settings. In this paper, we conceptually study and compare various types o...

The whole word recognition process described in this report aims at limiting the recognition domain, i.e. the size of the lexicon used for a particular word. The process consists of the following stages: • calculating the word zoning information and the position of ascenders/descenders within the word; • building word shape information using the obtained zoning information; • locating words of ...

This paper describes an approach to automatically detect stance in tweets by building a supervised system combining shallow features and pre-trained word vectors as word representation. The word vectors were obtained from several collections of large corpora using GloVe, an unsupervised learning algorithm. We created feature vectors by selecting the word vectors relevant to the data and summing...

Text corpus size is an important issue when building a language model (LM). This is a particularly important issue for languages where little data is available. This paper introduces an LM adaptation technique to improve an LM built using a small amount of task dependent text with the help of a machine-translated text corpus. Icelandic word error rate experiments were performed using data, mach...

This paper presents a current status of Thai resources and tools for CG development. We also proposed a Thai categorial dependency grammar (CDG), an extended version of CG which includes dependency analysis into CG notation. Beside, an idea of how to group a word that has the same functions are presented to gain a certain type of category per word. We also discuss about a difficulty of building...

In this paper building statistical language models for Persian language using a corpus and incorporating them in Persian continuous speech recognition (CSR) system are described. We used Persian Text Corpus for building the language models. First we preprocessed the texts of corpus by correcting the different orthography of words. Also, the number of POS tags was decreased by clustering POS tag...