[PDF] Top 20 Unsupervised Multilingual Grammar Induction

... We investigate the task of unsupervised constituency parsing from bilingual par- allel corpora. Our goal is to use bilin- gual cues to learn improved parsing mod- els for each language and to evaluate these models ... See full document

... Of the meta-heuristics that use more than a stan- dard, scalar objective, deterministic annealing (DA) (Rose, 1998) is closest to lateen EM. DA perturbs objective functions, instead of manipulating solu- tions directly. ... See full document

... the unsupervised induction of grammar is still a key open problem in machine learning, it is not for lack of trying: at least since (Solomonoff, 1964), much talent and effort has been invested in ... See full document

... So far, we only have four PFSTGs, with different segment lengths. We did not carry out all possible experiments, but the ones we did carry out all show that splitting helps (all models in Table 1 with an s followed by ... See full document

... We have performed other experiments using this representation and search algorithm, on tasks in unsupervised learning from speech and grammar induction.. Figure 5 contains a small portio[r] ... See full document

... A number of successful unsupervised raw-text syntax induction systems also exist. Seginer (2007) (CCL) uses a non-probabilistic scoring system and a dependency-like syntactic representation to bracket ... See full document

... duces multilingual word embeddings that are com- petitive with the state of the art in bilingual lexicon ...of multilingual dependency parsing and ... See full document

... Conditional description length (CDL) is a general method for evaluating a model and a dataset given a preexisting model. This makes it ideal for augment- ing an existing model with a variant model of the same family. In ... See full document

... In unsupervised grammar induction, data like- lihood is known to be only weakly cor- related with parsing accuracy, especially at convergence after multiple ...large multilingual ... See full document

... Grammar induction using bilingual parallel cor- pora has been studied mainly in machine transla- tion research (Wu, 1997; Melamed, 2003; Eisner, 2003; Chiang, 2005; Blunsom et ... See full document

... With a Tag Dictionary We also ran a second ver- sion of each experimental configuration, where we used a tag dictionary to restrict the possible path se- quences of the HMM during both learning and infer- ence. This tag ... See full document

... One of the advantages of the prototype driven ap- proach, over a fully unsupervised approach, is the ability to refine or add to the annotation specifica- tion if we are not happy with the output of our sys- tem. ... See full document

... We investigate an unsupervised learning method for dependency parsing models that imposes spar- sity biases on the dependency types. We assume a corpus annotated with POS tags, where the task is to induce a ... See full document

... evaluate unsupervised algo- rithms only using syntactically annotated data for evaluation and not for ...into unsupervised grammar and POS in- duction holds considerable promise, although cur- rent ... See full document

... gual grammar induction that exploits a phylogeny-structured model of parameter ...the multilingual model substan- tially outperforms independent learning, with larger gains both from more articu- ... See full document

... al (2012) trains a latent non-probabilistic discrim- inative model for preordering as an ITG-like gram- mar limited to binarizable permutations. Tromble and Eisner (2009) use ITG but do not train the grammar. They ... See full document

... Unsupervised grammar induction has been an ac- tive area of research in computational linguistics for over twenty years (Lari and Young, 1990; Pereira and Schabes, 1992; Charniak, ... See full document

... In practice, we rarely have complete data to train on, so we need our models to generalize to unseen data. A model that is very certain about the training data runs the risk of not being able to generalize to new data: ... See full document

... and multilingual set- ...the multilingual setting we trained them on the combined training data of all the 15 languages and tested on one of the ...lingual grammar model (G) performs better on av- ... See full document

... Various alternatives to EM were explored by Smith (2006), achieving substantially more accu- rate parsing models by altering the objective func- tion. Smith’s methods did require substantial hyper- parameter tuning, and ... See full document