基于数据驱动的语音库的分析与构建

语音数据库和规则库是转换系统中最基本和重要的部分,在进行转换时,根据韵律建模的结果,从原始语音库中取出相应的语音基元,利用特定的语音合成技术对基元进行韵律调整合成。针对语音数据库和规则库的建立技术,在GPS嵌入式系统的语音库构建过程中,在与传统方法比较的基础上,给出了基于数据驱动的构建方法,并在特定平台RAM10上,对“文-语”转换技术中的瓶颈之一进行了探讨和实践。     

紫外-可见光谱测定马尾松纸浆树脂中甘油三酯含量

用紫外光谱法测定马尾松TMP浆和酸性亚硫酸盐浆正己烷抽出物中甘油三酯的含量,探讨了三油酸甘油酯标准物与纸浆树脂的紫外吸光谱图特征与特征峰位置以及测试时间对吸光度值的影响。结果表明,在实验试剂用量范围内,三油酸甘油酯在412 nm的吸光度与浓度成线性关系,线性相关系数为0.971;吸光度随测试时间呈线性降低关系,相关系数为0.990。再现性实验回收率98％～104％,精确度1.27％～4.03％。利用该方法测定了纸浆与酶处理后纸浆抽提物中甘油三酯的含量,评价了酶处理纸浆降解甘油酯的效果。马尾松TMP与酸性亚硫酸盐浆中甘油三酯含量较高,约占总抽提物的50％。酶处理后TMP浆与酸性亚硫酸盐浆中甘油三酯降解率分别达到46.31％和35.55％。     

Combination of pitch synchronous analysis and fisher criterion for speaker identification

A novel text independent speaker identification system is proposed. In the proposed system, the 12-order perceptual linear predictive cepstrum and their delta coefficients in the span of five frames are extracted from the segmented speech based on the method of pitch synchronous analysis. The Fisher ratios of the original coefficients then be calculated, and the coefficients whose Fisher ratios are bigger are selected to form the 13-dimensional feature vectors of speaker. The Gaussian mixture model is used to model the speakers. The experimental results show that the identification accuracy of the proposed system is obviously better than that of the systems based on other conventional coefficients like the linear predictive cepstral coefficients and the Mel-frequency cepstral coefficients.     

基于SHS的重叠语音基音分离检测方法

运用SHS(分谐波累加)法可准确地提取单个语音的基音周期,本文将该方法推广运用到重叠语音基音的分离检测,并提出了相应的检测方法.实验证明,本文提出的方法能有效地分离并提取两重叠语音的基音,即使对于基音周期相差较近的两个重叠语音也能取得较好的结果.     

基于预搜索策略的ACELP语音编码算法

基于预搜索策略的ACELP语音编码算法     

基于小波变换的汉语声调识别新方法

利用小波变换能够模拟人耳听觉特性的优点及其时频局部化特性,对实际语音信号进行分析。根据小波变换模极大值原理以及语音信号的奇异和瞬态特性,提出了一种新的小波变换峰值检测算法。该算法可用于精确提取语音的基音周期,准确进行声调识别。最后,给出应用实例说明了本文算法的有效性。     

On a Pitch Alteration for Speech Synthesis Systems

Speech synthesis can be classified into waveform coding, source coding, or hybrid coding by the synthesis method. Among these, waveform coding is especially suitable for high-quality speech synthesis. However, synthesis techniques using syllable or phoneme unit is not desirable since it fails to separate the excitation and the formant part to handle speech. Therefore, there is a need for a pitch alteration method to apply in synthesis using waveform coding. This study proposes a pitch alteration method that uses spectrum scaling after flattening the spectra by a sub-band linear approximation to minimize the spectrum distortion. A comparison with LPC (Linear Predictive Coding), Cepstrum and lifter function is presented to show the better performance of the proposed method. Estimation method seeks each of the distributions of the flattened signal and measures the degree of the flattened spectrum Signal, which is normalized, so the highest point amounts to zero, and the distribution of the signal, whose average is zero, is calculated. The results are presented by the spectrum distortion rate to estimate the performance of the proposed method. The average spectrum distortion rate kept below the average 2.12%, showing the proposed method’s superiority in comparison with the other existing approaches.

On a Speech Multiple System Implementation for Speech Synthesis

This paper proposes a voice synthesizer to convert a single speech to multiple speeches. Pitch is an important voice characteristic of speech parameter and it is produced by the periodic vibration of the vocal-cords; the parameter most sensitive for human’s auditory sense. So if you change the pitch of the voice with several different scaling rates, you can produce several different voices at the same time with a voice. The Multiple-Speech Synthesizer will be used in diverse practical applications. The cheer synthesizer that makes group voice from a single voice would be such an example. You could also use the system for a troll toy, birthday song tracks, effect sounds in movies and plays, protection systems of houses, etc. Furthermore, the synthesizer could be used to imitate the voice of famous entertainers or cartoon characters, such as the Mask-man.

基于归一化自相关的语音基频特征提取

语音的基频（也称音高、基音周期或F0）及其变化规律是语音信号的一个重要特征,在语音情绪识别、声纹识别中有重要的应用。而语音基频的提取一直是语音信号处理中的难点,这也是语音基频特征未能广泛应用于语音识别等应用的重要原因,因此准确高效的提取音高在语音信号处理中能够有重要的意义。本文基于归一化自相关函数,结合倒频谱方法,提取了一种改进的基于归一化自相关的语音基频提取算法,实验证明该方法在基频提取中取得了较好的结果。