Disambiguating the senses of non-text symbols for Mandarin TTS systems with a three-layer classifier

Yu, Mei; Huang, Feng-Long

doi:10.1016/s0167-6393(02)00015-8

Cited by 12 publications

(1 citation statement)

References 8 publications

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“…One such category contains articles that used Bayesian models in relation to speech or image recognition. These articles included theoretical models of human speech or image recognition, as well as computational models for image and speech recognition (e.g., Yu & Huang, 2003). Another small category deals solely with Bayes Factors, which are calculated from the ratio of BICs for two models, as described by Kass and Raftery (1995; see, for example, Cipora & Nuerk, 2013).…”

Section: Resultsmentioning

confidence: 99%

A systematic review of Bayesian articles in psychology: The last 25 years.

Schoot

Winter

Ryan

et al. 2017

Psychological Methods

297

212

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Although the statistical tools most often used by researchers in the field of psychology over the last 25 years are based on frequentist statistics, it is often claimed that the alternative Bayesian approach to statistics is gaining in popularity. In the current article, we investigated this claim by performing the very first systematic review of Bayesian psychological articles published between 1990 and 2015 (n = 1,579). We aim to provide a thorough presentation of the role Bayesian statistics plays in psychology. This historical assessment allows us to identify trends and see how Bayesian methods have been integrated into psychological research in the context of different statistical frameworks (e.g., hypothesis testing, cognitive models, IRT, SEM, etc.). We also describe take-home messages and provide "big-picture" recommendations to the field as Bayesian statistics becomes more popular. Our review indicated that Bayesian statistics is used in a variety of contexts across subfields of psychology and related disciplines. There are many different reasons why one might choose to use Bayes (e.g., the use of priors, estimating otherwise intractable models, modeling uncertainty, etc.). We found in this review that the use of Bayes has increased and broadened in the sense that this methodology can be used in a flexible manner to tackle many different forms of questions. We hope this presentation opens the door for a larger discussion regarding the current state of Bayesian statistics, as well as future trends. (PsycINFO Database Record

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Section: Resultsmentioning

confidence: 99%