描述部分信用语音识别分数与β-二项式分布的相关性
1Center for Hearing Research, Boys Town National Research Hospital, Omaha, Nebraska 68131, USAadam.bosen@boystown.org.
JASA express letters
|February 1, 2024
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.
- 这些发现对于耳植入物研究中的准确测量至关重要.
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