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Description: 检测语音信号的共振峰
％ gender = gender_detector(X,Fs)
％
％ This function will use a pitch detection algorithm to decide if the speaker is MALE(0) or FEMALE (1).
％ It is designed to work with short speech samples (up to or greater than 50 ms). The function returns a
％ 0 if X contains male speech and a 1 if it contains female speech.
-the resonance peak gender_detector% gender = (X, Fs)%% This function will use a detection a pitch lgorithm to decide if the speaker is abbreviation (0) or F EMALE (1). % It is designed to work with short spe ech samples (up to or greater than 50 ms). The fun ction returns a 0% if X contains a male speech and if it contains a female speech.
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Size: 16251 |
Author: lixiao |
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Description: 检测语音信号的共振峰
％ gender = gender_detector(X,Fs)
％
％ This function will use a pitch detection algorithm to decide if the speaker is MALE(0) or FEMALE (1).
％ It is designed to work with short speech samples (up to or greater than 50 ms). The function returns a
％ 0 if X contains male speech and a 1 if it contains female speech.
-the resonance peak gender_detector% gender = (X, Fs)%% This function will use a detection a pitch lgorithm to decide if the speaker is abbreviation (0) or F EMALE (1). % It is designed to work with short spe ech samples (up to or greater than 50 ms). The fun ction returns a 0% if X contains a male speech and if it contains a female speech.
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Size: 16384 |
Author: lixiao |
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Description: VB实现的语音识别与合成的程序集,其中包括语音控制Flash动画的例子，需要用到Microsoft Speech SDK5.1语音工具包http://www.microsoft.com/speech/download/上可免费下载,为了能够支持中文识别与合成，还必须下载Language Pack-VB realize the speech recognition and synthesis procedures for collection, including voice control of Flash animation examples, the need to use Microsoft Speech SDK5.1 voice http://www.microsoft.com/speech/download/ Toolkit can be downloaded free of charge, Chinese in order to be able to support the identification and synthesis, also must download the Language Pack
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Size: 833536 |
Author: lilybxyz |
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Description: The speech signal contains rich messages, and three main recognition fields from speech signal, which are of most interest and have been studied for several decades, are speech recognition, language recognition and speaker recognition. In this the focus is on speech recognition field. In our everyday lives there are many forms of communication, for instance: body language, textual language, pictorial language and speech, etc. However amongst those forms speech is always regarded as the most powerful form because of its rich dimensions character. Except for the speech text (words), the rich dimensions also refer as the gender, attitude, emotion, health situation and identity of a speaker. Such information is very important for an effective communication. From the signal processing point of view, speech can be characterized in terms of the signal carrying message information. The waveform could be one of the representations of speech, and this kind of signal has been most useful in practical applications.
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Size: 3072 |
Author: kinny garg |
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Description: 本文是关于基于性别识别的语音识别方法综述及介绍-This article is about the recognition of gender-based Speech Recognition Techniques and Introduction
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Size: 168960 |
Author: yangqian |
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Description: 进行采样语音信号，计算出基频，从而判断出性别。-Sampled speech signal to calculate the fundamental frequency, which determine gender.
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Size: 97280 |
Author: susuwen |
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Description: speech gender voice recognition
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Size: 3072 |
Author: llorch |
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Description: 循环amdf算法实现语音性别识别，为研究语音性别识别的学者提供了一份参考资料。-Circulation amdf algorithm to realize gender recognition for research, speech recognition scholars speech gender provides a reference material.
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Size: 153600 |
Author: wangqipeng |
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Description: 建立了普通话语音性别数据库,提出联合梅尔频率频谱系数(Mel2f requency Cep st rum
Coefficient s , MFCC) 的特征提取方法和支持向量机(Support Vector Machine , SVM) 的分类方法进行说话人性别识别,并与其它分类方法进行比较。-A Chinese speech ( mandarin ) database was established for speaker s gender recognition. A
combination met hod is p roposed for gender recognition of speaker s based on support vector machine and
Mel2f requency cep st rum coefficient s (MFCC) for classification and feat ure ext raction respectively.
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Size: 303104 |
Author: wangqipeng |
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Description: Record your voice for 5 seconds
Play back the recording
Store data in double-precision array
Plot the waveform
Calculate over all the frames in the sample
LPF the speech at 900 Hz to remove upper freq. (since Pitch info. will be below 900 Hz)
Perform Centre Clipping and find the Clipping Level (CL)
Choose the appropriate clipping level
Perform Center clipping
Compute the autocorrelation
calcute pitch
Calculate the avg. pitch estimate for the whole sample X.
Find Gender - Record your voice for 5 seconds
Play back the recording
Store data in double-precision array
Plot the waveform
Calculate over all the frames in the sample
LPF the speech at 900 Hz to remove upper freq. (since Pitch info. will be below 900 Hz)
Perform Centre Clipping and find the Clipping Level (CL)
Choose the appropriate clipping level
Perform Center clipping
Compute the autocorrelation
calcute pitch
Calculate the avg. pitch estimate for the whole sample X.
Find Gender
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Size: 2048 |
Author: sido |
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Description: Abstract—Several algorithms have been developed for tracking
formant frequency trajectories of speech signals, however most of
these algorithms are either not robust in real-life noise environments
or are not suitable for real-time implementation. The algorithm
presented in this paper obtains formant frequency estimates
voiced segments of continuous speech by using a time-varying
adaptive filterbank to track individual formant frequencies. The
formant tracker incorporates an adaptive voicing detector and a
gender detector for formant extraction continuous speech,
for both male and female speakers. The algorithm has a low signal
delay and provides smooth and accurate estimates for the first four
formant frequencies at moderate and high signal-to-noise ratios.
Thorough testing of the algorithm has shown that it is robust over
a wide range of signal-to-noise ratios for various types of background
noises.-Abstract—Several algorithms have been developed for tracking
formant frequency trajectories of speech signals, however most of
these algorithms are either not robust in real-life noise environments
or are not suitable for real-time implementation. The algorithm
presented in this paper obtains formant frequency estimates
voiced segments of continuous speech by using a time-varying
adaptive filterbank to track individual formant frequencies. The
formant tracker incorporates an adaptive voicing detector and a
gender detector for formant extraction continuous speech,
for both male and female speakers. The algorithm has a low signal
delay and provides smooth and accurate estimates for the first four
formant frequencies at moderate and high signal-to-noise ratios.
Thorough testing of the algorithm has shown that it is robust over
a wide range of signal-to-noise ratios for various types of background
noises.
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Size: 67584 |
Author: assouma |
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Description: voice/unvoiced speech, gender identification
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Size: 1223680 |
Author: shambhu |
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Description: The Code For Gender Identification for speech signals using Auto correlation method
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Size: 521216 |
Author: murthysrikanth
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