Location:
Search - ear in matlab
Search list
Description: 语音信号的频域处理,语音虽然是一个时变、非平稳的随机过程。但在短时间内可近似看作是平稳的。因此如果能从带噪语音的短时谱中估计出“纯净”语音的短时谱，即可达到语音增强的目的。由于噪声也是随机过程，因此这种估计只能建立在统计模型基础上。利用人耳感知对语音频谱分量的相位不敏感的特性，这类语音增强算法主要针对短时谱的幅度估计。
-voice signals in the frequency domain processing, voice is a time-varying, nonstationary random process. But in a short period of time can be approximated as smooth. So if Noisy Speech from the short-term spectrum estimate "pure" voice of the short-term spectrum, and reached speech enhancement purposes. As the noise is random process, which can only be estimated based on statistical models based on. Use ear perception of voice spectrum component of the phase sensitive to the characteristics of such speech enhancement algorithms targeted at the rate of short-term spectral estimation.
Platform: |
Size: 1024 |
Author: 罗飞 |
Hits:
Description: 基于改进LPCC和MFCC的汉语耳语音识别,在MATLAB上设计出了基于LPCC和MFCC的汉语语音孤立词识别/-LPCC and MFCC Based on Improved Chinese ear speech recognition, in the MATLAB design based on the LPCC and MFCC Chinese isolated word speech recognition /
Platform: |
Size: 344064 |
Author: chenfeng |
Hits:
Description: 线性判别分析（LDA）是一种较为普遍的用于特征提取的线性分类方法。但是将LDA直接用于人耳识别会遇到维数问题和“小样本”问题。人们经过研究，通过多种途径解决了这两个问题并实现了基于LDA的人耳识别。文章对几种基于LDA的人耳识别方法做了理论上的比较和实验数据的支持，这些方法包括Fisherears、DLDA、VDLDA及VDFLDA。实验结果表明VDFLDA是其中最好的一种方法
-Linear Discriminant Analysis (LDA) is a more common linear feature extraction for classification. LDA but used directly in the human ear to identify problems encountered dimension and the
Platform: |
Size: 2129920 |
Author: 冷福 |
Hits:
Description: MFCC参数很好的反映了人耳的听觉特性,所以在语音识别中我们也用到他,本代码是用matlab仿真了MFCC 参数的提取过程.-MFCC parameters well reflected the auditory characteristics of the human ear, so in speech recognition, we also used him, and this code is used matlab simulation parameters of the MFCC extraction process.
Platform: |
Size: 1024 |
Author: chengbin |
Hits:
Description: 国际会议上的关于人耳图像识别的论文：Multi-view Ear Recognition Based on B-Spline Pose Manifold Construction -Multi-view Ear Recognition Based on B-Spline Pose Manifold Construction
Platform: |
Size: 507904 |
Author: 王景涛 |
Hits:
Description: 用头相关传输函数卷积合成虚拟声的方法，我们将利用没有方位信息的单通道声音信号（可以是一段标准语音，也可以是音乐等其他类型的声音），通过信号处理的方法赋予其方位感。
人能听到声音是声音在空间中传播的结果，声音从声源到人耳鼓膜传播过程中发生了变化，这种变化可以看成是人双耳对声音的滤波作用，因此我们将声音从自由场传到鼓膜处的传输函数定义为头相关传输函数(HRTF, Head Related Transfer Function)，其对应的时域响应称为头相关冲激响应(HRIR, Head Related Impulse Response)。本实验用到的HRTF/HRIR数据库是由MIT Media Lab测量得到的。-Convolution with the head-related transfer function virtual sound synthesis approach, we will use the information without bearing single sound signal (can be a standard voice, can also be other types of music, sound), through signal processing methods to give its position sense.
One can hear the sound is sound in space, the spread of the sound the human ear from the sound source to spread the process of tympanic membrane changes, this change can be considered as one of the filtering effect of both ears to the voices, so we will sound from the spread to the tympanic membrane at the free field transfer function is defined as the head related transfer function (HRTF, Head Related Transfer Function), the corresponding time domain response is called head-related impulse response (HRIR, Head Related Impulse Response). The experiment used HRTF/HRIR database is measured by the MIT Media Lab s.
Platform: |
Size: 20643840 |
Author: tanii |
Hits:
Description: Ear recognition in matlab
Platform: |
Size: 1007616 |
Author: dex |
Hits:
Description: 太阳黑子是人们最早发现也是人们最熟悉的一种太阳表面活动。因为太阳内部磁场发生变化，太阳黑子的数量并不是固定的，它会随着时间的变化而上下波动，每隔一定时间会达到一个最高点，这段时间就被称之为一个太阳黑子周期。太阳黑子的活动呈现周期性变化是由施瓦贝首次发现的。沃尔夫 (R.Wolfer)继而推算出11年的周期规律。实际上，太阳黑子的活动不仅呈11年的周期变化，还有海耳在研究太阳黑子磁场分布时发现的22年周期；格莱斯堡等人发现的80年周期以及蒙德极小期等。由于太阳黑子的活动规律极其复杂，时至今日科学家们仍在努力研究其内在的规律和特性。事实上，对太阳黑子活动规律的研究不仅具有理论意义，而且具有直接的应用需求。太阳黑子的活动呈现周期性变化的，沃尔夫(R.Wolfer)根据在过去的288 年(1700年~1987 年)间每年太阳黑子出现的数量和大小的观测数据推算出11 年的周期规律。我们利用Matlab强大的数据处理与仿真功能，对Wolfer数进行功率谱密度分析从而可以得到对太阳黑子活动周期的结论。-It is the first discovered sunspots is the most familiar kind of solar surface activity. Because the magnetic field inside the sun changes, the number of sunspots is not fixed, it changes over time fluctuations, the time intervals to reach a high point, this time it was called a sunspot cycle. Cyclical changes in sunspot activity first discovered by Schwabe. Wolf (R. Wolfer) and then calculate the 11-year cycle rule. In fact, sunspot activity was not only the 11-year cycle, as well as sea-ear magnetic field distribution in the study of sunspots and found a 22-year cycle Grameen Myers, who found 80-year cycle and the Maunder minimum, etc. . Because the law is extremely complex sunspot activity, scientists are still working today to study its internal rules and features. In fact, the laws of sunspot activity on the study not only of theoretical significance, but also has direct application requirements. Cyclical changes in sunspot activity, and Wolf (R. Wolfer) based in the past 288 yea
Platform: |
Size: 53248 |
Author: leeyoung |
Hits:
Description: 语音识别MFCC特征提取matlab代码。 「梅尔倒频谱系数」（Mel-scale Frequency Cepstral Coefficients，简称MFCC），是最常用到的语音特征，此参数考虑到人耳对不同频率的感受程度，因此特别适合用在语音辨识。-Speech recognition MFCC feature extraction matlab code. \ Mel cepstrum coefficient (Mel- scale Frequency Cepstral Coefficients, MFCC), is the most commonly used to the phonetic characteristics of this parameter given ear to the feelings of different frequencies, so especially suitable for use in speech recognition
Platform: |
Size: 1024 |
Author: Katherine |
Hits: