Redundancy-free Island Parsing of Word Graphs
نویسنده
چکیده
Island parsing is a bidirectional parsing strategy mostly used in speech analysis, as well as in applications where robustness is highly relevant and/or processing resources are limited. Although there exists an efficient redundancy-free island parsing algorithm for string input, it has not yet been applied to word graph input, an application which is central for speech analysis systems. This paper describes how the established algorithm can be generalized from string input to word graphs, increasing its flexibility by integrating the selection of island seeds into the search process inherent to parsing.
منابع مشابه
تأثیر ساختواژهها در تجزیه وابستگی زبان فارسی
Data-driven systems can be adapted to different languages and domains easily. Using this trend in dependency parsing was lead to introduce data-driven approaches. Existence of appreciate corpora that contain sentences and theirs associated dependency trees are the only pre-requirement in data-driven approaches. Despite obtaining high accurate results for dependency parsing task in English langu...
متن کاملTitle Consideration on Syntactic Analyses for a Speech
SUMMARY In this paper, we compared the left-to-right & top-down parsing strategy with the island-driven & botom-up strategy by using a simulated phoneme recognizer. The both strategies adopted the beam search. The syntactic constraints were represented by a context-free grammar. The word lattice for an utterrance was generated by a word spotting algorithm from an ambiguous phoneme sequence. The...
متن کاملStructural Parsing
In the theory of knowledge graphs, words are represented by word graphs. Sentences are to be represented by sentence graphs. This is called structural parsing. Under consideration of the semantic and syntactic features of natural language, both semantic and syntactic word graphs are formed, the latter expressing the function of word types like nouns, verbs, etc. Traditional grammar rules can be...
متن کاملBreaking the barrier of context-freeness
This paper presents a generative probabilistic dependency model of parallel texts that can be used for statistical machine translation and parallel parsing. Unlike syntactic models that are based on context-free dependency grammars, the dependency model proposed in this paper is based on a sophisticated notion of dependency grammar that is capable of modelling non-projective word order and isla...
متن کاملTime Mapping with Hypergraphs
Word graphs are able to represent a large number of different utterance hypotheses in a very compact manner. However, usually they contain a huge amount of redundancy in terms of word hypotheses that cover almost identical intervals in time. We address this problem by introducing hypergraphs for speech processing. Hypergraphs can be classified as an extension to word graphs and charts, their ed...
متن کامل