嵌入式语音识别的前后端处理关键技术研究

在语音识别技术的研究中，语音端点检测和拒识是语音前后端处理的关键技术。在噪声环境下，传统的过零率和短时能量的端点检测效果会变得很差；频域的端点检测方法虽然较时域的端点检测方法鲁棒性更高，但是它需要进行大量的计算不能很好地满足嵌入式系统。针对嵌入式系统的特点，为提高语音识别能力，提出了基于统计理论的孤立词的端点检测算法，在一个相对较长的时间段内语音信号服从正态分布，而噪音信号主要存在于信号均值的一定方差范围之内。方法既满足了嵌入式系统的计算要求，又有一定鲁棒性。

Research on Key Technologies of Front-end and Back-end for Embedded Automatic Speech Recognition

Speech endpoint detection and out-of-vocabulary rejection are two important parts of the whole automatic speech recognition process.The performance of traditional speech endpoint detection based on short-term energy and zero-crossing rate becomes very poor in noisy environments,and sometimes even unable to work.Methods based on frequency-domain need complex computing,and it can not meet embedded systems well.In this paper a new endpoint detection algorithm is presented,which is based on statistical theory f...