Analysis of short‐time speech transmission index algorithms
Analysis of short‐time speech transmission index algorithms
复制标题
短时语音传输指标算法分析
DOI：
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发表时间：
2008
期刊：
影响因子：
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通讯作者：
Mona Shrestha
中科院分区：
文献类型：
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作者：
K. Payton;Mona Shrestha
已有多种方法使用语音作为探针刺激来计算语音传输指数 (STI)（Goldsworthy & Greenberg, J. Acoust. Soc. Am., 116, 3679‐3689, 2004）。频域方法虽然可以准确预测长期 STI，但无法预测由于背景波动而导致的短期变化。时域方法也适用于长语音片段，并且具有用于短时分析的附加潜力。本研究调查了两种时域 STI 方法的准确性：包络回归 (ER) 和归一化相关 (NC)，作为窗口长度的函数，在具有多个说话者和说话风格的各种声学退化环境中。将短时 STI 与短时理论 STI 进行比较，后者源自倍频程信噪比和混响时间。对于短至 0.3 秒的窗口，ER 和 NC 方法跟踪短时理论 STI，并且对于大于 4 的窗口，理论和 ER 方法都收敛到长期结果...
Various methods have been shown to compute the Speech Transmission Index (STI) using speech as a probe stimulus (Goldsworthy & Greenberg, J. Acoust. Soc. Am., 116, 3679‐3689, 2004). Frequency‐domain methods, while accurate at predicting the long‐term STI, cannot predict short‐term changes due to fluctuating backgrounds. Time‐domain methods also work well on long speech segments and have the added potential to be used for short‐time analysis. This study investigates the accuracy of two time‐domain STI methods: envelope regression (ER) and normalized correlation (NC), as functions of window length, in various acoustically degraded environments with multiple talkers and speaking styles. Short‐time STIs are compared with a short‐time Theoretical STI, derived from octave‐band signal‐to‐noise ratios and reverberation times. For windows as short as 0.3 s, the ER and NC Methods track the short‐time Theoretical STI and both the Theoretical and ER Methods converge to the long‐term result for windows greater than 4 ...
影响因子：
2.4
作者：
Goldsworthy, RL;Greenberg, JE
通讯作者：
Greenberg, JE
影响因子：
2.4
作者：
Payton, KL;Braida, LD
通讯作者：
Braida, LD