Апостериорные вероятности

method ID: posteriorprobabilities

Related Papers

Comparing and Combining Generative and Posterior Probability Models: Some Advances in Sentence Boundary Detection in Speech

Authors: nan

Publication: TIPSTER (2004)

DOI: nan

We compare and contrast two different models for detecting sentence-like units in continuous speech. The first approach uses hidden Markov sequence models based on N-grams and maximum likeli- hood estimation, …...

44013

Discriminative state tracking for spoken dialog systems

Authors: nan

Publication: TIPSTER (2013)

DOI: nan

In spoken dialog systems, statistical state tracking aims to improve robustness to speech recognition errors by tracking a posterior distribution over hidden dialog states. Current approaches based on gener- ative …...

40243

A Dynamic Programming Algorithm for Computing N-gram Posteriors from Lattices

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

Efficient computation of n-gram posterior probabilities from lattices has applications in lattice-based minimum Bayes-risk de- coding in statistical machine translation and the estimation of expected document frequencies from spoken corpora. …...

34260

Neural Lattice-to-Sequence Models for Uncertain Inputs

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

AbstractThe input to a neural sequence-to-sequence model is often determined by an up-stream system, e.g. a word segmenter, part of speech tagger, or speech recognizer. These up-stream models are potentially …...

32943