Knowledge-Based Analysis of Speech Mixed with Steady and Sporadic Environmental Sounds

这是一个探索性研究（SGER）项目的小额赠款。该项目研究了在任意环境中使用来自稳定和零星背景噪声源的知识的可行性，这些噪声源发生在不受语音识别条件限制的任意环境中，以将它们与识别任务中与说话人无关的电话号码发音隔离开来。环境噪声背景存在于家庭、办公室和汽车中；稳态噪声的类型包括来自空调或汽车发动机的噪声，而零星噪声源是离散的事件，如人走路、关门、电话铃响或电器开机。该问题是在信号理解体系结构的基础上解决的，该体系结构具有上下文相关的特征提取过程重构。从第一轮特征提取的结果进行分析的时频区域与系统的知识关于各种语音和非语音源的相关性一致。在预测可能出现在话语其他部分的非言语来源可能掩盖的言语时，要考虑那些较高确定性的区域或确定性岛屿。这些区域也被用作特征提取过程重构的基础，用于分析被掩盖区域以及验证、修剪和精炼所有区域的假设。综上所述，虽然系统的目标是识别语音，但它还必须对非语音进行识别，以帮助语音识别过程。//

This is a Small Grant for Exploratory Research (SGER) project. The project investigates the feasibility of using knowledge from the steady and sporadic background noise sources that occur in arbitrary environments not conditioned for speech recognition to isolate them from speaker-independent articulation of telephone numbers in a recognition task. The environmental noisy background could be found in home, offices, and automobiles; the types of steady-state noise include those originating from an air conditioner or from a car engine, while the sporadic noise sources are discrete events such as a person walking, a door slammed, a ringing telephone, or an appliance being switched on. The problem is addressed on the basis of a signal-understanding architecture with context-dependent reconfiguration for the feature extraction process. The results from an initial round of feature extraction are analyzed for time-frequency regions consistent with the system's knowledge regarding the correlates of various speech and non-speech sources. Those regions of higher certainty - or islands of certainty - are considered in the prediction of potentially masked speech by non-speech sources that may occur in other parts of the utterance. Those regions are used also as a basis in the reconfiguration of the feature-extraction process which is used in analyzing the masked region as well as in verifying, pruning, and refining hypotheses in all regions. In summary, while the goal of the system is to recognize speech, it must also perform the recognition on non-speech sounds to help the speech recognition process. //