Viterbi Algorithm

In this paper a new, tree-trellis based fast search for finding the N best sentence hypotheses in continuous speech recognition is proposed. The search consists of two parts: a forward, …...

° • We present an iterative procedure to build a Chinese language model (LM). We seg- ment Chinese text into words based on a word-based Chinese language model. How- ever, …...

This paper presents a novel statistical model for automatic identification of English baseNP. It uses two steps: the N- best Part-Of-Speech (POS) tagging and baseNP identification given the N-best POS-sequences. …...

Part of speech taggers based on Hidden Markov Models rely on a series of hypothe- ses which make certain errors inevitable. The idea developed in this paper consists in allowing …...

Letter-substitution ciphers encode a docu- ment from a known or hypothesized lan- guage into an unknown writing system or an unknown encoding of a known writing system. It is a …...

The Viterbi algorithm is the conventional decoding algorithm most widely adopted for sequence labeling. Viterbi decoding is, however, prohibitively slow when the label set is large, because its time com- …...

We propose a novel forest reranking algorithm for discriminative dependency parsing based on a variant of Eisner’s generative model. In our framework, we define two kinds of gener- ative model …...

This paper proposes a multi-objective opti- mization framework which supports heteroge- neous information sources to improve align- ment in machine translation system combi- nation techniques. In this area, most of …...

Bidirectional models of word alignment are an appealing alternative to post-hoc combinations of directional word align- ers. Unfortunately, most bidirectional formulations are NP-Hard to solve, and a previous attempt to …...

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, …...

AbstractThe linear-chain Conditional Random Field (CRF) model is one of the most widely-used neural sequence labeling approaches. Exact probabilistic inference algorithms such as the forward-backward and Viterbi algorithms are typically …...