Dynamic Programming

MLR, an extended LR parser, is introduced, and its application to natural language parsing is discussed. An LR parser is a ~;hift-reduce parser which is doterministically guided by a parsing …...

Speaker independent phonetic Iranscription of fluent speech is performed using an ergodic continuously variable duration hidden Markov model (CVDHMM) to represent the acoustic, phonetic and phonotactic structure of speech. An …...

The Context-Free backbone of some natural language ana- lyzers produces all possible CF parses as some kind of shared forest, from which a single tree is to be chosen by …...

AbstractWe present JANUS, a speech-to-speech translation system that utilizes diverse processing strategies including connectionist learning, traditional AI knowledge representation approaches, dynamic programming, and stochastic techniques. JANUS translates continuously spoken English …...

Parsing a long sentence is very difficult, since long sentences often have conjunctions which result in am- biguities. If the conjunctive structures existing in a long sentence can be analyzed …...

The speech understanding system we propose in this paper is based on the stochastic modeling of a sentence as a sequence of elemental units that represent its meaning. According to …...

This paper addresses the alignment issue in the framework of exploitation of large bi- multilingual corpora for translation purposes. A generic alignment scheme is proposed that can meet varying requirements …...

Machine translation (MT) systems do not currently achieve optimal quality trans- lation on free text, whatever translation method they employ. Our hypothesis is that the quality of MT will improve …...

Experiences in computing alignments at the paragraph and sentence level within a project TRANSLEARN in the European Union's "LRE" programme of research and development in language engineering are reported. About …...

Alignment methods based on byte-length comparisons of alignment blocks have been remarkably successful for aligning good translations from legislative transcriptions. For noisy translations in which the parallel text of a …...

Research in example-based machine translation (F,I~MT) has been hampered by the lack of efficient tree alignment al- gorithms for bilingual corpora. *ghis pa- per <lescribes an alignment algorithm for F,I~MT …...

This paper snggests a method to align Korean-English parallel corpus. '1?he structural dissimilarity between Korean and Indo-European languages requires more flexible measures to evaluate the alignment candidates between the bilin- …...

This paper describes a method for the automatic align- ment of parallel texts at clause level. The method fea- tures statistical techniques coupled with shallow linguis- tic processing. It presupposes …...

The errors in Chinese document are mainly caused in two stages - input and editing. There are homonyms or homophones selection error, ambiguous pronunciation error, word segmentation error, similar shape …...

AbstractIn this paper we describe a language recognition algorithm for multilingual documents that is based on mixed-order n-grams, Markov chains, maximum likelihood, and dynamic programming. We present the results of …...

In a text-to-speech (TTS) conversion system based on the time-domain pitch-synchronous overlap-add (TD-PSOLA) method, accurate estimation of pitch periods and pitch marks is necessary for pitch modification to assure an …...

In this paper we introduce a dynamic programming algorithm to perform lin- ear text segmentation by global mini- mization of a segmentation cost function which consists of: (a) within-segment word …...

This paper describes log-linear pars- ing models for Combinatory Categorial Grammar (CCG). Log-linear models can easily encode the long-range dependen- cies inherent in coordination and extrac- tion phenomena, which CCG …...

We present a novel discriminative approach to parsing inspired by the large-margin criterion underlying sup- port vector machines. Our formulation uses a factor- ization analogous to the standard dynamic programs …...

We present a method for speeding up the calculation of tree kernels during train- ing. The calculation of tree kernels is still heavy even with efficient dynamic pro- gramming (DP) …...

. In an EBMT system, we will meet the word sense disambiguation problem. The disambiguation methods used at present can’t be used easily in EBMT. We propose a new method …...

In this paper, we present an algorithm for learning a generative model of natural lan- guage sentences together with their for- mal meaning representations with hierarchi- cal structures. The model …...

We present a discriminative structure- prediction model for the letter-to-phoneme task, a crucial step in text-to-speech process- ing. Our method encompasses three tasks that have been previously handled separately: input …...

We describe a parsing approach that makes use of the perceptron algorithm, in conjunction with dynamic programming methods, to recover full constituent-based parse trees. The formalism allows a rich set …...

We introduce cube summing, a technique that permits dynamic programming algo- rithms for summing over structures (like the forward and inside algorithms) to be extended with non-local features that vio- …...

We present an inference algorithm that orga- nizes observed words (tokens) into structured inflectional paradigms (types). It also natu- rally predicts the spelling of unobserved forms that are missing from …...

We develop a general dynamic programming technique for the tabulation of transition-based dependency parsers, and apply it to obtain novel, polynomial-time algorithms for parsing with the arc-standard and arc-eager models. …...

Most existing systems solved the phrase chunking task with the sequence labeling approaches, in which the chunk candidates cannot be treated as a whole during parsing process so that the …...

Traditional general readability methods tend to underperform in domain-specific document retrieval because they fail to effectively differentiate the reading difficulty of the individual domain-specific terms and the semantic associations between …...

We present the first provably optimal polyno- mial time dynamic programming (DP) algo- rithm for best-first shift-reduce parsing, which applies the DP idea of Huang and Sagae (2010) to the …...

Current Translation Memory (TM) sys- tems work at the surface level and lack se- mantic knowledge while matching. This paper presents an approach to incorpo- rating semantic knowledge in the …...

Cross-narrative temporal ordering of med- ical events is essential to the task of gen- erating a comprehensive timeline over a patient’s history. We address the prob- lem of aligning multiple …...

AbstractLeft-to-right (LR) decoding Watanabe et al. (2006) is a promising decoding algorithm for hierarchical phrase-based translation (Hiero) that visits input spans in arbitrary order producing the output translation in left …...

. We present DYALOG-SR, a statistical dependency parser developed for the SPRML 2013 shared task over 9 very different languages. DYALOG-SR implements a shift-reduce parsing algorithm (a la MALT), extended …...

We propose a novel model for parsing natural language sentences into their for- mal semantic representations. The model is able to perform integrated lexicon ac- quisition and semantic parsing, mapping …...

Feature-Rich Space Carlos A. Colmenares∗ Google Inc. Brandschenkestrasse 110 8002 Zurich, Switzerland crcarlos@google.com Marina Litvak Shamoon College of Engineering Beer Sheva, Israel marinal@sce.ac.il Amin Mantrach Fabrizio Silvestri Yahoo Labs. Avinguda …...

The success of deep learning often de- rives from well-chosen operational build- ing blocks. In this work, we revise the temporal convolution operation in CNNs to better adapt it to …...

We present the first dynamic programming (DP) algorithm for shift-reduce constituency parsing, which extends the DP idea of Huang and Sagae (2010) to context-free grammars. To alleviate the propagation of …...

Modeling relation paths has offered sig- nificant gains in embedding models for knowledge base (KB) completion. How- ever, enumerating paths between two en- tities is very expensive, and existing ap- …...

Word embedding has been widely studied and proven helpful in solving many natural lan- guage processing tasks. However, the ambi- guity of natural language is always a prob- lem on …...

AbstractIn this paper, we propose a new decoding method for phrase-based statistical machine translation which directly uses multiple preordering candidates as a graph structure. Compared with previous phrase-based decoding methods, …...

Chinese character riddle is a riddle game in which the riddle solution is a single Chi- nese character. It is closely connected with the shape, pronunciation or meaning of Chi- …...

AbstractDecoding of phrase-based translation models in the general case is known to be NP-complete, by a reduction from the traveling salesman problem (Knight, 1999). In practice, phrase-based systems often impose …...

AbstractPruning hypotheses during dynamic programming is commonly used to speed up inference in settings such as parsing. Unlike prior work, we train a pruning policy under an objective that measures …...

AbstractWe study a formalization of the grammar induction problem that models sentences as being generated by a compound probabilistic context free grammar. In contrast to traditional formulations which learn a …...

AbstractMany common character-level, string-to-string transduction tasks, e.g., grapheme-to-phoneme conversion and morphological inflection, consist almost exclusively of monotonic transduction. Neural sequence-to-sequence models with soft attention, non-monotonic models, outperform popular monotonic models. …...

AbstractRetrieve-and-edit based approaches to structured prediction, where structures associated with retrieved neighbors are edited to form new structures, have recently attracted increased interest. However, much recent work merely conditions on …...

AbstractRhetorical Structure Theory (RST) parsing is crucial for many downstream NLP tasks that require a discourse structure for a text. Most of the previous RST parsers have been based on …...

AbstractRecognizing the flow of time in a story is a crucial aspect of understanding it. Prior work related to time has primarily focused on identifying temporal expressions or relative sequencing …...

AbstractReinforcement learning has been proved to be effective in handling low resource machine trans-lation tasks and different sampling methods of reinforcement learning affect the performance ofthe model. The reward for …...

AbstractThe sentence is a fundamental unit in many NLP applications. Sentence segmentation is widely used as the first preprocessing task, where an input text is split into consecutive sentences considering …...