There are different approaches to the problem of assigning each word of a text with a parts-of-speech tag, which is known as Part-Of-Speech (POS) tagging. In this paper we compare the performance of a few POS tagging techniques for Bangla language, e.g. statistical approach (n-gram, HMM) and transformation based approach (Brill’s tagger). A supervised POS tagging approach requires a large amoun...

This paper presents a stochastic model of French intonation contours for use in text-to-speech synthesis. The model has two modules, a linguistic module that generates abstract prosodic labels from text, and a phonetic module that generates an F0 curve from the abstract prosodic labels. This model differs from previous work in the abstract prosodic labels used, which can be automatically derive...

We introduce a simple wrapper method that uses off-the-shelf word embedding algorithms to learn task-specific bilingual word embeddings. We use a small dictionary of easily-obtainable task-specific word equivalence classes to produce mixed context-target pairs that we use to train off-the-shelf embedding models. Our model has the advantage that it (a) is independent of the choice of embedding a...

It has been argued that, when learning a first language, babies use a series of small clues to aid recognition and comprehension, and that one of these clues is word length. In this paper we present a statistical part of speech tagger which trains itself solely on the number of letters in each word in a sentence.

This paper describes a variety of methods for inserting phrase boundaries in text. The methods work by ex­ amining the likelihood of a phrase break occurring in a sequence of three part-of-speech tags. The paper explains this basic technique and desribes more sophisticaed vari­ ations using distance probabilities.

The aim of this dissertation is to study statistical methods for multilingual word segmentation and POS tagging with high accuracy. Word segmentation and part-of-speech (POS) tagging are fundamental language analysis tasks in natural language processing, and used in many applications. Existence of unknown words is a large problem in these tasks and they need to be properly handled. We attempt t...

We propose a novel semantic tagging task, sem-tagging, tailored for the purpose of multilingual semantic parsing, and present the first tagger using deep residual networks (ResNets). Our tagger uses both word and character representations, and includes a novel residual bypass architecture. We evaluate the tagset both intrinsically on the new task of semantic tagging, as well as on Part-of-Speec...

We present a survey of tagging accuracies — concerning part-of-speech and full morphological tagging — for several taggers based on a corpus for medieval church Latin (see www.comphistsem.org). The best tagger in our sample, Lapos, has a PoS tagging accuracy of close to 96% and an overall tagging accuracy (including full morphological tagging) of about 85%. When we ‘intersect’ the taggers with ...

1 Last week: stochastic part-of-speech tagging Last week we reviewed parts-of-speech, which are linguistic categories of words. These categories are defined in terms of syntactic or morphological behaviour. Parts-of-speech for English traditionally include: Nouns are concrete or abstract entity; Pronouns substitute for nouns; Adjective modify nouns; Verbs are actions or states of being; Adverbs...

This paper proposes an improvement of the Brill’s “TransformationRule Based” POS-Tagger Algorithm. Our improvement decreases training times considerably without affecting the accuracy of the algorithm.