片语

speech blind signal语音盲信号

Sychronous Speech-Signal Capture同步语音数据采集

Speech Signal Hearing Threshold语音信号听觉门限

Speech communication signal语音通信信号

speech signal collection语音信号采集

Chinese speech digital signal processing汉语语音数字信号处理

speech digital signal processing语音数字信号处理

speech signal processing br语音信号处理

speech blind signal separation语音盲信号

英汉例句

• Speech recognition is a hot issue in the field of speech signal processing, and always is difficult, especially for the independent person in the noisy environment.

  语音识别是语音信号处理领域的研究热点，它长期以来一直是一项难题，尤其是对于噪声环境下以及非特定人语音识别。

• Use the predominance of new programmable logic chip on digital signal domain lucubrate on the implement with FPGA of speech signal low bit rate coding.

  本文利用新一代可编制逻辑器件在数字信号处理领域的优势，对语音信号低码率编码的FPGA实现进行了深入研究。

• Traditional speech signal processing is based on FFT power spectral analysis, in noisy condition, the spectrum of noise and speech signal are processed in the same way.

  传统语音信号谱特征的提取是基于FFT 的能谱分析方法，在噪音环境情况下，对噪音的频谱成分与语音信号的频谱成分的处理采用「平均主义」的原则。

• The function of the speech processor lies in dealing with speech signal and producing the pulse which electrodes need to stimulate cochlea.

  语音处理器主要作用在于声音的采集处理和产生电极所需的电刺激信号。

• Speech recognition, which focuses on speech as object, is an important research direction of speech signal processing and a primary technology to realize the communication between human and machines.

  语音识别是以语音为研究对象，是语音信号处理的一个重要研究方向，是实现人机通信的主要技术。

• Based on the speech produce model, we find the reason of periodicity disappearance and the extremum number increase by analysing the character of speech signal when the glottal closes.

  于是从语音产生模型入手，详细的分析了声门闭合时刻语音信号的性质，找到了浊音信号经过小波变换后周期性消失、极值点个数增多的原因。

• The quality of speech signal is affected to decline quickly by high noises, so controlling noise, speech distortion and improving speech intelligibility have become central aims.

  由于语音信号的质量常常由于高噪声的影响而急剧下降。因此，抑制噪声，有效控制失真度和人为噪声，并提高语音可懂度成为首要任务。

• Finally, expects future application and progress of fractal theory in speech signal processing.

  最后对分形理论在语音信号处理中的应用与发展进行了展望。

• And the second part introduces the characteristics of speech signal and some key technique.

  第二章则介绍语音信号的特性和处理的一些关键技术。

• To get the pitch of a speech remains an unsolved but basic problem in the field of speech signal process.

  基音周期的确定是语音处理领域中的一个尚未完全解决的基本问题。

• A noise reduction algorithm used in speech signal processes which is referred to as LMS adaptive noise reduction, is also designed to reduce wide-band noise but improve signal to noise Ratio.

  此外本文还设计一种语音信号自适应噪声消除算法，利用LMS自适应算法的特点抑制语音信号中的宽带噪声信号，提高信噪比。

• The endpoint detection technology of speech signal is to accurately determine starting point and ending point from a section of speech signal. Thus it can distinguish speech and non-speech signal.

  语音信号的端点检测技术就是从包含语音的一段信号中準确地确定语音的起始点和终止点，区分语音和非语音信号。

• In this paper, we use full pole model to obtain speech signal LPC, then deduce it「s LPCC, and we use the LPCC difference to describe speaker」s track dynamic movement.

  本文应用全极点模型，提取语音信号的线性预测系数，并推导出其倒谱系数，获得线性预测倒谱差分，用以描述说话人声道的动态变化。

• It presents a new method on reducing additive white noise in speech signal using linear prediction error.

  在此提出一种利用线性预测误差去除语音中的加性白噪声的方法。

• Then the speech signal is pitch adjusted according to this pitch contour, where the original signal with time varying pitch period is converted to a signal of constant pitch period.

  然后根据这一轨迹对语音信号进行「基音调整」，将原始的、具有时变基音周期的信号转化为一个具有恒定基音周期的信号。

• The speech source localization technology based on microphone array has been abroad applied to communication and speech signal processing.

  基于麦克风阵列的声源定位技术在通信、语音处理等领域得到广泛的应用。

• If the wavelet transform is directly implemented in pitch detection, comparing the glottal closure singularity of speech signal with image grey break, we will not obtain the anticipative result.

  将声门闭合在语音信号中表现出相应的奇异性，与图像边缘的灰阶突变进行等价对比，直接将小波变换用于声门闭合奇异型的检测，并不会得到预期效果。

• People are no longer satisfied with the simple speech signal and transmission of the characters data, But expect that uses many kinds of expression media.

  人们不再满足于单纯的语音信号和文字数据的传输，而是期盼使用多种表示媒体。

• So, in this chapter, the basic principle and algorithm of LPC for speech signal have been discussed in detail.

  所以这一章较为详细地讨论了语音信号线性预测编码的基本原理和算法。

• A speech signal is basically a sequence of sounds that is strung together to represent a thought that a speaker wishes to convey to a listener.

  总的来说，一个语音信息就是连起来的一连串声音，用来表达说话者想要传递给听者的一个想法。

• The speech signal is a kind of typical non-stationary signal.

  语音信号是一种典型的非平稳信号。

• A new approach which exploits the distribution properties of speech signal for vector quantization of speech signal is proposed in the paper.

  本文提出了一种利用语音信号分布特性的矢量量化方法。

• In this paper we introduce a speech signal processing platform.

  本文介绍一种语音信号处理工作平台。

• The proposed method uses the maximum singular value of an cumulant matrix to distinguish between voiced parts of the speech signal and noise.

  提出一种采用累积量矩阵的最大奇异值来实现语音端点检测的方法，并引入一种自适应的实现方法。

• As the commonest and most direct method for information expression, the speech signal is widely used in many fields.

  语音信号作为信息的最普遍最直接的表达方式，在许多领域具有广泛的应用前景。