Жасырын Марков модельдері

This paper reports on two contributions to large vocabu- lary continuous speech recognition. First, we present a new paradigm for speaker-independent (SI) training of hid- den Markov models (HMM), which …...

In this paper we present preliminary results obtained at Dragon Systems on the Resource Maaaagernent benchmark task. The basic conceptual units of our system are Phonemes-m-Context (PICs), which are represented …...

The BYBLOS continuous speech recognition system is applied to on-line cursive handwriting recognition. By exploiting similarities between on-line cursive handwriting and continuous speech recogni- tion, we can use the same …...

This paper introduces a class of statistical mechanisms, called hidden understanding models, for natural language processing. Much of the framework for hidden understanding models derives from statistical models used in …...

Preparation, recording, segmentation and pitch labelling of Slovenian diphone inventories are described. A special user friendly intert'ace package was developed in order to facilitate these operations. As acquisition of a …...

This article attempts to determine what ele- ments of linguistic theory are used in statisti- cal language learning, and why the extracted language models look like they do. The study …...

We present a technique which complements Hidden Markov Models by incorporating some lexicalized states representing syntactically un- common words. 'Our approach examines the distribution of transitions, selects the uncom- mon …...

We consider the problem of modeling the con- tent structure of texts within a specific do- main, in terms of the topics the texts address and the order in which …...

Spelling recognition is an approach to enhance a speech recognizer’s ability to cope with incorrectly recognized words and out-of-vocabulary words. This paper presents a general framework for Thai speech recognition …...

. We present the current status of development of an open-source shallow-transfer machine translation engine for the Romance languages of Spain (the main ones being Span- ish, Catalan and Galician) …...

In this paper we propose a methodology for sen- timent analysis of figurative language which ap- plies Word Sense Disambiguation and, through an n-gram graph based method, assigns polar- ity …...

AbstractCorpus-based dialogue systems rely on statistical models, whose parameters are inferred from annotated dialogues. The dialogues are usually annotated in terms of Dialogue Acts (DA), and the manual annotation is …...

AbstractCurrent state-of-the-art systems for automatic phonetic transcription (APT) are mostly phone recognizers based on Hidden Markov models (HMMs). We present a different approach for APT especially designed for transcription with …...

A variety of information extraction techniques rely on the fact that instances of the same relation are “distributionally similar,” in that they tend to appear in similar textual con- texts. …...

This paper discusses two Hidden Markov Models (HMM) for linking linguistically motivated XTAG grammar and the auto- matically extracted LTAG used by MICA parser. The former grammar is a detailed …...

Segmental evaluation of HTS HTS is a parametric speech synthesis system based on the use of Hidden Markov Models (HMM). HTS is now widely used but very few studies have …...

We present a method for exact optimization and sampling from high order Hidden Markov Models (HMMs), which are generally han- dled by approximation techniques. Motivated by adaptive rejection sampling and …...

Recent work has explored the use of hidden Markov models for unsupervised discourse and conversation modeling, where each seg- ment or block of text such as a message in a …...

Toward an acoustic to articulatory inversion of a foreign speaker We present an extension of our acoustic-to-articulatory inversion method, based on unsupervised Hidden Markov Models. The articulatory vectors’ generation is …...

Despite significant recent work, purely unsu- pervised techniques for part-of-speech (POS) tagging have not achieved useful accuracies required by many language processing tasks. Use of parallel text between resource-rich and …...

A key challenge for computational conver- sation models is to discover latent struc- ture in task-oriented dialogue, since it pro- vides a basis for analysing, evaluating, and building conversational systems. …...

For annotation tasks involving independent judgments, probabilistic models have been used to infer ground truth labels from data where a crowd of many annotators labels the same items. Such models …...

We propose a fast and scalable method for semi-supervised learning of sequence models, based on anchor words and moment matching. Our method can handle hidden Markov mod- els with feature-based …...

AbstractWeighted finite automata and transducers (including hidden Markov models and conditional random fields) are widely used in natural language processing (NLP) to perform tasks such as morphological analysis, part-of-speech tagging, …...

This paper describes a small but unique digitized collection of medieval Latin charters. This collection consists of 57 charters of 7 types illustrating various purposes of issuance by the Royal …...

AbstractProbabilistic finite-state automata are a formalism that is widely used in many problems of automatic speech recognition and natural language processing. Probabilistic finite-state automata are closely related to other finite-state …...

AbstractWord alignments identify translational correspondences between words in a parallel sentence pair and is used, for instance, to learn bilingual dictionaries, to train statistical machine translation systems, or to perform …...

AbstractSpeech is considered as a multi-modal process where hearing and vision are two fundamentals pillars. In fact, several studies have demonstrated that the robustness of Automatic Speech Recognition systems can …...

AbstractNamed entity recognition generally refers to entities with specific meanings in unstructured text, including names of people, places, organizations, dates, times, quantities, proper nouns and other words. In the medical …...