We propose a probabilistic model for estimating word confidence by fusing predictor features. Starting from the maximum entropy (ME) method, we first prove ...
We propose a probabilistic model for estimating word confidence by fusing predictor features. Starting from the maximum entropy (ME) method, we first prove ...
ABSTRACT. We propose a probabilistic model for estimating word confi- dence by fusing predictor features. Starting from the Maxi- mum Entropy (ME) method, ...
In this paper, we present several confidence measures for large vocabulary continuous speech recognition. We propose to estimate the confidence of a ...
A Hidden-State Maximum Entropy Model Forword Confidence Estimation. Exploiting Uncertainties for Binaural Speech Recognition · An Auditory Neural Feature ...
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The Maximum Entropy Model is defined as a model that maximizes entropy while satisfying statistical constraints by assuming the network state probability ...
Missing: Forword Estimation.
We investigate the problem of using continuous features in the maximum entropy (MaxEnt) model. We explain why the MaxEnt model with the moment constraint ( ...
May 30, 2024 · This work investigates the confidence estimation methods for LLMs in generating structured data. Through experiments, we find LLM internal ...
Information extraction techniques automati- cally create structured databases from un- structured data sources, such as the Web or newswire documents.
Given a model form, we choose values of parameters λi to maximize the. (conditional) likelihood of the data. • For any given feature weights, we can calculate:.