Highly spectrally undersampled vowels can be classified by machines without supervision
نویسندگان
چکیده
منابع مشابه
Learning to be Bayesian without Supervision
Bayesian estimators are defined in terms of the posterior distribution. Typically, this is written as the product of the likelihood function and a prior probability density, both of which are assumed to be known. But in many situations, the prior density is not known, and is difficult to learn from data since one does not have access to uncorrupted samples of the variable being estimated. We sh...
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ژورنال
عنوان ژورنال: The Journal of the Acoustical Society of America
سال: 2019
ISSN: 0001-4966
DOI: 10.1121/1.5111154