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相关概念视频

Binomial Probability Distribution01:15

Binomial Probability Distribution

10.8K
A binomial distribution is a probability distribution for a procedure with a fixed number of trials, where each trial can have only two outcomes.
The outcomes of a binomial experiment fit a binomial probability distribution. A statistical experiment can be classified as a binomial experiment if the following conditions are met:
There are a fixed number of trials. Think of trials as repetitions of an experiment. The letter n denotes the number of trials.
There are only two possible outcomes,...
10.8K
Expected Frequencies in Goodness-of-Fit Tests01:19

Expected Frequencies in Goodness-of-Fit Tests

2.5K
A goodness-of-fit test is conducted to determine whether the observed frequency values are statistically similar to the frequencies expected for the dataset. Suppose the expected frequencies for a dataset are equal such as when predicting the frequency of any number appearing when casting a die. In that case, the expected frequency is the ratio of the total number of observations (n)  to the number of categories (k).
2.5K
Confidence Coefficient01:24

Confidence Coefficient

7.6K
The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under...
7.6K
Prediction Intervals01:03

Prediction Intervals

2.3K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y. 
2.3K
Bonferroni Test01:10

Bonferroni Test

2.7K
The Bonferroni test is a statistical test named after Carlo Emilio Bonferroni, an Italian mathematician best known for Bonferroni inequalities. This statistical test is a type of multiple comparison test to determine which means are different than the rest. Bonferroni test can minimize the Type 1 error by reducing the significance level alpha, which otherwise increases with sample pairs.
The means of different samples are first paired in all possible combinations.
The null hypothesis of the...
2.7K
Probability Distributions01:32

Probability Distributions

7.0K
 The probability of a random variable x  is the likelihood of its occurrence. A probability distribution represents the probabilities of a random variable using a formula, graph, or table. There are two types of probability distribution– discrete probability distribution and continuous probability distribution.
A discrete probability distribution is a probability distribution of discrete random variables. It can be categorized into binomial probability distribution and Poisson...
7.0K

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相关实验视频

Updated: Jul 4, 2025

Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody
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Foreign Accent and Forensic Speaker Identification in Voice Lineups: The Influence of Acoustic Features Based on Prosody

Published on: September 27, 2024

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描述部分信用语音识别分数与β-二项式分布的相关性.

Adam K Bosen1

  • 1Center for Hearing Research, Boys Town National Research Hospital, Omaha, Nebraska 68131, USAadam.bosen@boystown.org.

JASA express letters
|February 1, 2024
PubMed
概括

部分信用评分可以提高语音识别精度. 然而,情境线索会产生准确度的相关性,这必须在耳植入物用户的统计功率分析中加以解决.

科学领域:

  • 听觉神经科学 听觉神经科学
  • 语音处理 语音处理
  • 统计建模 统计建模

背景情况:

  • 部分信用评分可以提高语音识别中的测量精度.
  • 评估这种改进是复杂的,因为上下文的线索在令牌识别概率中创造了相关性.

研究的目的:

  • 使用β-双项分布估计语音识别准确度和类内相关性.
  • 为耳植入器听众研究词语中的音符和句子中的词语中的这些相关性.

主要方法:

  • 利用β-双项分布来建模识别准确度.
  • 在20名耳植入物使用者中分析了语音和文字识别.
  • 计算了在刺激中识别准确性的类内相关系数.

主要成果:

  • 在刺激中的识别准确度中显示出实质性的类内相关性.
  • 发现这些相关性在各个参与者之间是不变的.
  • 突出了上下文线索对语音识别数据的影响.

结论:

  • 语音识别准确度的类内相关性在个人中是显著和一致的.
  • 这些相关性需要在部分信用评分的权力分析中考虑.

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  • 这些发现对于耳植入物研究中的准确测量至关重要.