摘要
语音通信是人类最常见最有效的通信方式,随着数字化信息化时代的飞速发展,已经实现了实时的、超远距离的语音通信,人们对于语音通信的音质也越来越高,然而,电磁空间各频段分布日趋密集,语音信号在传输过程中常受到各类电磁信号的干扰,加之声源处的各种噪声干扰并放大,甚至在军用领域对于非合作信号的提取,往往都是淹没在极强干扰的背景之下。尽可能地将微弱的语音信号从复杂的噪声环境中提取出来,会便于民用通信,更好地获得军事情报等。而自然界最为普遍的分布就是高斯分布,本文假设强干扰背景信号是服从高斯分布的,以尽可能多地符合真实场景,再利用同步累加的算法,使得服从高斯分布的强背景噪声在一定程度上抵消,而含有用信息的语音信号在多次叠加后相对于背景噪声更加突出,进而容易提取。
Voice communication is the most common and most effective communication method of human beings. With the rapid development of digital information age, real-time and ultra-long distance voice communication has been realized, and our request for the the sound quality of voice communication is also getting higher and higher. However, the distribution of the electromagnetic space is becoming increasingly dense, and in the transmission process, the voice signal is often subject to various types of electromagnetic interference, coupled with the noise at the sound source and amplification. Even non-coop- erative signal extraction in the military field, voice with information often be submerged under the background of strong in- terference. Extracting weak voice signal from the complex noise environment as far as possible, will facilitate civilian com- munications, and access to military intelligence better, etc. The most common distribution of nature is the Gaussian distribu- tion. In this paper, it is assumed that the strong interference background signal obeys the Gaussian distribution to meet the real scene as much as possible, and then use the algorithm of synchronous accumulation to make the strong background noise which obeys Gaussian distribution offset to a certain extent. And the speech signal that contains the useful information is more prominent than the background noise after repeated stacking. In this way, it is easy to extract.
出处
《电声技术》
2017年第7期117-121,共5页
Audio Engineering
关键词
高斯约束
强干扰
微弱信号
语音信号
同步累加
提取
Gaussian constraints
strong interference
weak signal
speech signal
synchronous accumulation
extraction
