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A Study on Alternative Speech Sensor

机译:替代语音传感器的研究

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This paper presents a study on alternative speech sensor for speech processing applications. Noise robustness is one of the major considerations in speech processing systems. In presence of noise, speech signal renders unintelligible naturally and thus degrades the performance of automatic speech recognition systems. Close-talk microphone perfums well for clean speech signals. The close-talk microphone based recognition performance fails under real non-stationary conditions and also degraded strongly by the background noise. One way of improving such a system performance is by the use of alternative sensors, which are attached to the speaker's skin and receive the uttered speech through throat or bones. There are two types of sensors namely alternative acoustic and non-acoustic sensors. First, alternative acoustic sensors are more isolated from environmental noise and pick up the speech signal in a robust manner. Second is to develop noisy robust speech recognition system using Multi-sensor approach. This approach combines the information from different sources of acoustic speech sensors. The thirdinvolves non-acoustic speech sensors, which are primarily used for speaker identification task and some speech recognition applications. Fourth, discusses the speech enhancement methods for the noisy speech signal. These approaches help to improve the speech recognition system in noisy conditions and lead to building a robust ASR system.
机译:本文介绍了用于语音处理应用的替代语音传感器的研究。噪声稳健性是语音处理系统中的主要考虑因素之一。在存在噪声时,语音信号自然地造成不可忽视的,从而降低自动语音识别系统的性能。闭合谈话麦克风精美,用于清洁语音信号。基于闭合麦克风的识别性能在真正的非静止条件下失败,并且通过背景噪声强烈地降低。改进这种系统性能的一种方法是使用替代传感器,该传感器连接到扬声器的皮肤上并通过喉部或骨骼接收发出的语音。有两种类型的传感器即替代的声学和非声学传感器。首先,替代的声学传感器从环境噪声中分离出来,并以稳健的方式拾取语音信号。其次是使用多传感器方法开发嘈杂的鲁棒语音识别系统。该方法将来自来自声学语音传感器的不同来源的信息组合。三个非声学语音传感器,主要用于扬声器识别任务和一些语音识别应用。第四,讨论了嘈杂语音信号的语音增强方法。这些方法有助于改善嘈杂的条件中的语音识别系统,并导致构建强大的ASR系统。

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