It is essential for speech processing system to have robust speech detection.
可靠的语音检测是实现可靠的语音处理系统的关键。
Two new speech detection methods based on neural networks using Barker coded synchronization signal are presented.
提出了两种采用巴克码编码同步信号并基于神经网络的起点检测新方法。
First, the traditional speech detection method based on short-time energy is discussed, including its principle and implementation.
本文的具体研究工作主要有以下几个方面：首先，讨论了传统的基于能量的起点检测方法。
Adaptive algorithm of speech detection based on statistical classification is presented to reduce the dependence of the training data.
该文针对统计分类语音算法对训练数据的依赖问题，提出自适应算法在线动态更新分类模型。
VAD algorithm based on RASTA-filter multi-dimensional speech feature and Support Vector Machine is presented. It applies to the speech detection under the low SNR conditions.
提出了一种基于RASTA滤波技术的多维语音特征和支持向量机分类的VAD算法，适用于低信噪比情况下的话音检测。
This paper researches on speech detection algorithm based on time domain, and describes an adaptive, both forwards and backwards search, detecting short-term pulse noise algorithm.
本文探讨了基于时域的语音切分算法，在前人研究的基础上，提出一种改进算法——自适应、前后搜索和检测短时脉冲噪音算法。
The endpoint detection is important in speech recognition.
端点检测是语音识别中重要的一环。
A major cause of errors in speech recognition is the inaccurate detection of word boundary.
词边界检测误差是语音识别中产生错误的主要原因之一。
The endpoint detection based on short-time average magnitude of speech signals relative autocorrelation sequences can be detected in high accuracy under the low signal-to noise ratio.
在较低信噪比情况下，基于语音信号的短时相对自相关序列的短时平均幅度的端点检测能够获得较高的检测精度。
The accuracy of the speech endpoint detection is important to the recognition performance.
语音端点检测的准确性直接影响着语音识别系统性能。
Searching for the methods of acoustic evaluation and phonatory detection has become the focused problem by doctors in otorhinolaryngology and speech pathology.
对嗓音评估、发音功能检测方法的研究已成为耳鼻喉科医生、音声言语疾病学科医生共同关注的问题。
This paper analyzes speech endpoint detection based on short-term energy feature in the presence of noise.
研究了噪声环境下，利用短时能量为特征进行语音端点检测的问题。
In the paper, a speech endpoint detection method based on DCT (Discrete Cosine Transform) enhancement and improved spectral entropy is proposed.
提出了基于DCT(离散余弦变换)增强和改进谱熵的语音端点检测方法。
A Marine engine room detection system is designed with speech synthesis chip and single-chip microcomputer as main hardware.
本文以语音合成芯片和单片机为主要硬件，设计了一种船舶机舱检测系统。
The autocorrelation pitch detection algorithm is the key technique for speech signal processing, and its efficiency directly affects the quality of real-time speech processing.
自相关基音检测算法是语音信号处理的关键技术，算法的效率直接影响语音信号实时处理的质量。
In the research of mixed excitation linear prediction speech coding, a new real-time normalized correlation function pitch detection algorithm is proposed.
在混合激励线性预测低速率语音编码研究中，提出了一种新的归一化自相关函数实时基音检测算法。
The main speech signal endpoint detection methods, such as short time energy based scheme, HMM based scheme, related alike scheme and so on are investigated deeply.
对语音信号端点检测的主要方法，如基于短时能量的方法、基于HMM的方法、基于自相关相似距离的方法等进行了深入研究。
In speech signal processing, one of the key technologies is the pitch detection algorithm, and its efficiency directly affects the quality of speech's real-time processing.
自相关基音检测算法是语音信号处理的关键技术，算法的效率直接影响了语音信号实时处理的质量。
Doubletalk detection(DTD) is used to sense whether the far-end speech is corrupted by the near-end speech in echo cancellation.
声回波对消中，双端语音检测用以判定远端语音是否混和有近端语音。
In order to provide an accurate-pitch-cycle speech for pith detection algorithm with varied noise and SNR, we use signal decomposition theory in pre-processing of pitch detection.
为了在不同噪声、信噪比下为基音检测算法提供更能准确反映基音周期实际变化的输入语音，本文将信号分解思想引入基音检测前端处理中。
The former includes Chinese word segmentation, part - of - speech tagging, pinyin tagging, named entity recognition, new word detection, syntactic parsing, word sense disambiguation, etc.
前者涉及到词法、句法、语义分析，包括汉语分词、词性标注、注音、命名实体识别、新词发现、句法分析、词义消歧等。
Recent researches on speech model and decision rule improve the performance of voice activity detection.
各种改进算法针对语音模型、判决规则等核心问题进行了系统研究，检测性能得到了进一步提高。
The noise estimation is updated in both speech frame and noise frame without the voice activity detection.
不采用端点检测，在语音帧内及噪声帧内都进行噪声更新。
So we focus on the study of pitch detection algorithms for noisy speech and strive to find algorithms with relatively good accuracy and robustness.
为此，本论文就含噪语音进行基音检测算法的研究，力求寻找准确性和鲁棒性都相对较好的基音检测算法。
A major cause of errors in speech recognition is the inaccurate detection of word bound-ary. Conventional methods can not work well in the condition of low SNR and variable background noise level.
词边界检测误差是语音识别中产生错误的主要原因之一，常规的检测算法在低信噪比尤其在背景噪声能量可变的环境下不能有效工作。
In the same time, a sliding pitch analysis window method is used, so it can reduce the pitch detection error in non-stationary speech segments with irregular pitch.
同时又采用了滑动窗的方法，使得对基音周期不规则的不平稳的语音段进行基音周期估计时的误差减小。
Besides normal speech evaluation, error detection based on phoneme alignment and phoneme recognition was provided.
除了通常的发音评分外，还提供基于音素关联和音素识别的错误检测功能。
Firstly, the digital speech signal processing and some common speech endpoint detection methods are summarized and analysed. Some experiment results and improvements are also shown in the paper.
本文首先总结了语音信号数字化处理过程，分析了常用的几种端点检测方法，并给出了其实验结果与一些相应的改进。
Firstly, the digital speech signal processing and some common speech endpoint detection methods are summarized and analysed. Some experiment results and improvements are also shown in the paper.
本文首先总结了语音信号数字化处理过程，分析了常用的几种端点检测方法，并给出了其实验结果与一些相应的改进。
应用推荐