[PDF] Top 20 An Unsupervised Probability Model for Speech to Translation Alignment of Low Resource Languages

... We also compute F-scores for each Italian word type. As shown in Figure 3, the longer the word’s utterance, the easier it is for our model to correctly align it. Longer utterances seem to carry enough in- ... See full document

... Word alignment usually serves as the starting point and foundation for a statistical machine translation (SMT) ...final alignment for phrase training. The resource required for this approach ... See full document

... feasible model for machine translation. As for speech recognition, longer words are generally less prone to error (Shinozaki & Furui 2001); this accounts for the fact that under 70% word accuracy ... See full document

... machine translation (NMT) has recently proven success- ful (Eriguchi et ...for languages or domains for which a reliable parser is not ...an unsupervised tree-to-sequence (tree2seq) model for ... See full document

... Most of the papers surveyed above rely on auto- matic word alignments to guide the cross-lingual transfer of information. Given our desire to use highly multilingual information to improve pro- jection accuracy, the ... See full document

... world languages: (1) an online or hard-copy pocket-sized bilingual dictionary, (2) a basic library reference grammar, and (3) access to an existing monolingual text corpus in the ...generative model using ... See full document

... at low- resource cognate identification and word ...IBM alignment models, so future work could explore more advanced algorithms relat- ing to word alignment and machine translation, ... See full document

... Word alignment is considered to be an important step in training machine translation systems, since it helps to learn the correlations between the input and the output ...word alignment since they ... See full document

... these seed dictionaries. At this point, Equation 5 should produce reasonable alignments between the source languages and En, e.g., q(horse | magar) = 0.5, q(donkey | magar) = 0.3, q(cow | magar) = 0.2, where magar ... See full document

... target languages for which ei- ther little or no training data was ...main model, M A LOP A , that was meant to pro- duce reasonable parses for languages under “zero- resource” ...the ... See full document

... In this considering scenario, we need to identify a fixed set of intents related to a specific domain. Instead of converting these probability values into a text representation, we classify these obtained features ... See full document

... of speech data collected for language documentation and research re- main untranscribed and unsearchable, but often a small amount of speech may have text translations ...additional speech with ... See full document

... A number of tools and methodologies have been proposed for web scraping use in building web corpora for speech and NLP applications. Ba- roni and Bernardini (2004) developed BootCat to generate search engine ... See full document

... we model text as sequences of words, our model cannot produce any of the unseen word types in the test data and is penalized for this, but it can be trained very quickly (Bansal et ...instead model ... See full document

... Each consortium partner had a professional translator translate the sentences in the respective source languages (Greek, Dutch, German and Spanish) into English. To- gether with the original English sentence from ... See full document

... a model based on Vector-Quantized Auto- Encoders, VQ-VAE (van den Oord et ...Our model introduces residual con- nections parallel to the quantized ... See full document

... the alignment shown in Figure 3 revealing that the high tone word <bye> “seed” has a pitch contour about 20 mels higher than the known mid tone in the frame ...Forced alignment allows many such ... See full document

... for F (Hwa et al., 2002). The cohesion constraint requires that this induced dependency tree does not have any crossing dependencies. The details about how the cohesion constraint is implemented are out- side the scope ... See full document

... world’s languages, no structured, com- plete inflectional paradigms in a machine-readable format are available for human language technology (HLT) ap- ...15 languages, with materials ready for eliciting ... See full document

... of low- resource languages is to use resources from re- lated languages (Nakov and Ng, ...parent model on a (pos- sibly unrelated) high-resource language pair, then use this ... See full document