Splitting Input for Machine Translation Using N-gram Language Model Together with Utterance Similarity · Authors · Downloads · Published · Issue · Section.
In our splitting method, we generate candidates for utterance splitting based on N-grams, and select the best one by measuring the utterance similarity against ...
We use an N-gram Language Model (NLM) to gener- ate sentence-splitting candidates, and we use the. NLM and sentence similarity to select one of the.
In our splitting method, we generate candidates for utterance splitting based on N-grams, and select the best one by measuring the utterance similarity against ...
In this paper, to supplement N-gram based splitting methods, we introduce another clue using sentence similarity based on edit-distance. In our splitting method ...
Aug 23, 2004 · In this paper, to supplement N-gram based splitting methods, we introduce another clue using sentence similarity based on edit-distance. In our ...
Jun 23, 2009 · Converting an input file to an n-gram representation is just a way to put the data into a format for further feature analysis, but as you lose a ...
Missing: Utterance | Show results with:Utterance
Duration: 58:13
Posted: Dec 28, 2020
Posted: Dec 28, 2020
Missing: Splitting Input Utterance Similarity.
Jan 12, 2022 · Simply said, the language model should be good at predicting the next word given all previously transcribed words regardless of the audio input ...
NMT methods leverage the source-rich languages to improve the translation quality of resource-poor languages by using a universal model. Traditional MT methods ...