The Effectiveness of Oral Resonance Therapy on the Perception of Femininity of Voice in Male-to-Female Transsexuals

Ten male-to-female transsexuals participated in five sessions of oral resonance voice therapy targeting lip spreading and forward tongue carriage. Acoustic analysis of recordings made pre- and posttherapy found that participant formant frequency values (F1, F2, and F3, from the vowels /a/, /i/, and /mho/), as well as fundamental frequency (F0), underwent a general increase posttherapy. F3 values, in particular, increased significantly posttreatment. Trends in listener ratings of these recordings showed that the majority of participants were perceived to sound more feminine following treatment. Participants' self-ratings of their voices pre- and posttreatment also indicated that participants perceived their voices as sounding more feminine and that they were more satisfied with their voices following treatment. The present study supports the findings of previous studies that have demonstrated that resonance characteristics in male-to-female transsexuals can be changed to more closely approximate those of females through oral resonance therapy. This intervention study also demonstrates that a spontaneous increase in F0 is achieved during the course of therapy. Further, this study provides preliminary evidence to suggest that oral resonance therapy may be effective in increasing femininity of voice in male-to-female transsexual clients.     

Relationship Between Weight, Speaking Fundamental Frequency, and the Appearance of Phonational Gaps in the Adolescent Male Changing Voice

This 12-month prospective longitudinal study used acoustic analysis to identify phonational gaps in the vocal range of adolescent boys undergoing voice change and to investigate the relationship between the appearance of phonational gaps, weight gain, and changes in speaking fundamental frequency (SF0). Eighteen pubescent boys were recorded producing three descending and three ascending glides over their physiological voice range using the vowel "ah." Recordings were digitized over the range 0-16 kHz and then analyzed to determine both the frequency range and appearance and frequency characteristics of the phonational gaps. Data were plotted against changes in weight and SF0 both as an indicator of pubertal development and to test the hypothesis that changes in weight and SF0 were related to the appearance of phonational gaps. Results indicated that minimum F0 decreased significantly over the time period and phonational gaps increased significantly, but there were no significant changes in maximum F0 or range. Individual data indicated the initial appearance of a lower-frequency gap followed by a higher-frequency gap before the long-term establishment of a midrange gap. At time 5, all boys in the weight range 42.7-44.9 kg had either low- or high-range gaps. The SF0 for this group varied from 117 to 216 Hz. All boys heavier than 54.8 kg had highly variable phonational gaps. SF0 range for this group was 99.5-151 Hz. Transitory low- then high-frequency phonational gaps appeared before the establishment of a midrange phonational gap. In this study, these phonational gaps were associated with certain weight ranges and rapid weight gain, with changes to boys' speaking voices, and with loss of ability to use the mid- and falsetto vocal range.     

多源异构光谱信息融合的食用牛肝菌鉴别方法

牛肝菌营养丰富,味道鲜美,备受各国消费者青睐。因种间差异和环境因素的多层次影响,不同种类及产地牛肝菌品质参差不齐。目前,利益驱动导致商家在牛肝菌销售过程中以次充好、以假乱真的行为扰乱了食用菌市场,不仅给消费者带来健康风险,也制约了牛肝菌的国际化贸易。采用多源异构信息融合策略对牛肝菌种类与产地进行鉴别,以期为追溯食用菌来源以及正确评价其品质提供一种快速有效的解决方法。试验样品灰褐牛肝菌(Boletus griseus)、栗色牛肝菌(B. umbriniporus)、美味牛肝菌(B. edulis)、皱盖疣柄牛肝菌(Leccinum rugosicepes)和绒柄牛肝菌(B. tomentipes)五种牛肝菌科(Boletaceae)真菌子实体采于云南省保山市、昆明市、玉溪市与红河州。采用傅里叶变换红外光谱仪(FTIR)和紫外可见分光光度计(UV-Vis)采集样品信息。Kennard-Stone算法将样品原始数据分为校正集和验证集。校正集基于FTIR、UV-Vis、低级、中级与高级数据融合建立偏最小二乘判别分析(PLS-DA)模型,其中决定系数(R2_cal)、预测能力Q2、校正均方根误差(RMSEE)和交叉验证均方差(RMSECV)用来评价模型鲁棒性。研究结果显示：(1)不同种类及产地牛肝菌FTIR和UV-Vis吸收峰的峰位置、峰形和峰数相似,而吸收强度存有差异,表明牛肝菌所含化学成分相似,但含量有一定差别;(2)PLS-DA模型二维散点图可以看出,中级融合比低级融合能更好的鉴别样品种类及产地;(3)各模型中,中级融合模型具有更大的Q2和最小RMSECV,模型鲁棒性最强;(4)验证集样本用来验证模型泛化能力,FTIR、UV-Vis、低级融合、中级融合及高级融合模型样品种类鉴别正确率分别为92.86%,35.71%,97.62%,100%和95.23%;产地鉴别正确率分别为71.43%,61.90%,61.90%,97.62%和76.19%。表明多源异构信息融合在一定程度上优于独立模型,其中,中级数据融合种类鉴别正确率100%,产地鉴别正确率97.62%,模型具有更优的鉴别效果和泛化能力。FTIR和UV-Vis结合中级数据融合策略能实现牛肝菌种类快速精确鉴别,产地快速有效鉴别,可作为食用菌来源追溯以及品质评价的一种新方法。     

LIF技术与PLS-DA算法联合辨识矿井涌水水源类型的研究

快速的矿井涌水水源辨识对于矿井的水灾预警及灾后救援意义重大。常规方法使用离子浓度做为判别因子,耗时过长,因此提出一种激光诱导荧光光谱(LIF)技术与偏最小二乘判别分析(PLS-DA)算法联合快速辨识矿井涌水水源类型的方法。实验使用405 nm激光对被测水体进行激发,获取矿井5个不同含水层100组水样的荧光光谱,根据光谱曲线特征,对数据进行压缩处理,获取合适的光谱数据。每种水样使用15组共75组光谱数据作为建模集,剩余的25组水样的光谱数据作为测试集。为验证实验结果,设计了簇类的独立软模式(SIMCA)算法与PLS-DA算法构建的实验模型进行对比。实验发现矿井不同含水层水样的荧光光谱差异较大,在不进行任何预处理的情况下,以PLS模型为基础的PLS-DA算法较SIMCA算法的建模正确率高,达到了100%,其校正及验证结果与实际分类变量的相关系数均大于0.951,校正集均方根误差(RMSECV)和验证集均方根误差(RMSEP)均小于0.123,利用模型对测试集中五种水样样本的识别正确率均为100%。     

基于量子粒子群算法的混沌系统同步控制及参数辨识

针对异结构且参数未知混沌系统的同步控制,设计同步控制器并对误差系统的稳定性进行理论分析.通过合理选择优化目标函数,利用量子粒子群算法高效的全局寻优能力,实现混沌系统的未知参数辨识,有效降低同步控制器的开发难度.以Rössler混沌系统与Lorenz混沌系统的异结构同步为研究对象,进行数值仿真实验,结果表明该方法能够实现驱动-响应系统的快速混沌同步及系统未知参数的准确辨识,并验证该方法的可行性和有效性.     

基于高光谱图像的玉米种子特征提取与识别

玉米种子的形态特征是玉米品种识别的重要因素之一.采用高光谱成像系统获取9个品种共432粒玉米种子的高光谱反射图像,对图像进行校正和预处理,提取每个样本在563.6~911.4 nm共55个波段范围内的形状特征.分别利用单波段、多波段和全波段下的玉米种子形状特征结合偏最小二乘判别法进行模型分类.结果显示,全波段范围内训练集和测试集的平均正确识别率达到98.31%和93.98%,均优于多波段和单波段的正确识别率.研究表明,该方法能充分利用高光谱图像中可见光和近红外区域的有效特征信息,较准确地鉴别玉米品种,为玉米品种的自动识别领域提供了一种新方法.     

基于高光谱图像的玉米种子特征提取与识别

玉米种子的形态特征是玉米品种识别的重要因素之一.采用高光谱成像系统获取9个品种共432粒玉米种子的高光谱反射图像,对图像进行校正和预处理,提取每个样本在563.6～911.4nm共55个波段范围内的形状特征.分别利用单波段、多波段和全波段下的玉米种子形状特征结合偏最小二乘判别法进行模型分类.结果显示,全波段范围内训练集和测试集的平均正确识别率达到98.31%和93.98%,均优于多波段和单波段的正确识别率.研究表明,该方法能充分利用高光谱图像中可见光和近红外区域的有效特征信息,较准确地鉴别玉米品种,为玉米品种的自动识别领域提供了一种新方法.     

基于卷积神经网络与光谱特征的夏威夷果品质鉴定研究

夏威夷果含油量高,在开缝之后容易发生变质,现有关于夏威夷果品质鉴定的方法多为传统的破坏性检验,很难满足无损检测的需求。卷积神经网络(CNN)作为应用最广泛的深度学习网络模型之一,具有比浅层学习方法更强的特征提取与模型表达能力,在光谱数据方面的应用拥有很大潜力。基于夏威夷果在可见-近红外的光谱特征分析,研究用于提取夏威夷果光谱特征的卷积神经网络模型,并提出一种高效无损鉴定夏威夷果品质的方法。首先以三种不同品质的夏威夷果(好籽、哈籽及霉籽)为研究对象,分析样本在500~2 100 nm的光谱信息;在光谱数据预处理中引入白化处理方法,用以增强数据的相关性差异;然后在模型训练过程中,将样本随机分为训练集和预测集,探讨不同CNN结构、卷积层数、卷积核大小及个数、池化层类型、全连接层神经元个数以及激活函数对分类结果的影响,并采用激活函数ReLU和Dropout方法,预防样本数据过少引起的过拟合现象;最后通过分析模型分类准确率和计算效率,确定了一个6层结构的CNN模型： 输入层-卷积层-池化层-全连接层(200神经元)-全连接层(100神经元)-输出层。实验结果表明： 上述网络模型对校正集和预测集的分类准确率均达到100％。因此,改进后的卷积神经网络模型可充分学习夏威夷果的光谱特征并有效分类,将深度学习理论与光谱分析相结合的方法能够实现对夏威夷果品质的准确鉴定,同时为夏威夷果等坚果类食品的高效、无损、实时在线检测提供了新思路。     

近红外光谱和模式识别的菊花品种无损鉴别

菊花为菊科植物菊的头状花序,滁菊、贡菊、杭菊和亳菊是常见的几类药用品种菊花.不同品种菊花在外观上具有极大的相似性,非专业人员仅凭肉眼难以对其进行准确鉴别分析.常规仪器分析法检测成本较高,分析时间较长,且需要对样品进行破坏性处理,影响了产品的二次销售.近红外光谱技术作为近年来快速发展起来的一种绿色、简单、快速的新型检测技...     

Perceptual Identification and Acoustic Measures of the Resonant Voice Based on “Lessac''s Y-Buzz”—A Preliminary Study With Actors

This study aimed to verify whether the resonant voice based on Lessac's Y-Buzz can be perceived by listeners as resonant and different from habitual voice and to compare them to determine whether this sound exploration improves the vocal production. Nine newly graduated actors, six men and three women without voice complaints, were the subjects. They received a session of Lessac's Y-Buzz training from the primary investigator. Before training, they were asked to sustain the vowel /i/ at comfortable frequency and habitual loudness. After training, they were requested to sustain the Y-Buzz they had learned at a comfortable frequency and habitual loudness. Three speech-language pathologists (SLP) trained in voice developed an auditory-perceptive analysis. The pre- and posttraining voice samples were randomly spliced together, edited, and presented in pairs to perceptual judges who were asked to identify the most resonant of the pair. The voice samples were also acoustically compared through the Hoarseness Diagram and acoustic measures using the VoxMetria Software (CTS, version 2.0s, Brazil). The Y-Buzz trials were identified as resonant voice in 74% of the comparisons. The acoustic measures showed a statistically significant decrease of irregularity (P = 0.002) and shimmer (P = 0.38). The Hoarseness Diagram demonstrated how the resonant voice moved toward the normality for irregularity and noise components. The results showed that the resonant voice based on the Y-Buzz can be identified as resonant and different from normal voicing in the same subject, and it apparently implies a better vocal production demonstrating a significant decrease of shimmer and irregularity through the Hoarseness Diagram evaluation.     

基于OPO脉冲激光激发光声光谱的真假血液分类鉴别

为了实现快速准确并可回收再利用地鉴别真血和假血,采用光声光谱技术构建了一套血液光声检测系统并获取血样的光声信号.选取三种动物真血(马血、牛血和兔血)和两种假血(道具假血和红墨汁)共125组血样作为实验样本.获取了700～1064 nm波段内所有样本的光声信号和光声峰峰值谱.实验表明,真血和假血的光声信号幅度、轮廓、峰值...     

基于THz光谱成像的纸币真伪鉴别研究

根据纸币防伪特征区域载体材料与制作工艺的不同,利用透射式太赫兹脉冲成像技术对2005版真伪百元人民币的白水印和安全线两处防伪特征区域进行逐点扫描获取相应的太赫兹时域信号,然后对太赫兹波形进行数据处理获得时域显示模式成像及频域显示模式成像。将真钞和假钞的成像结果进行对比,发现白水印、安全线部位的真假钞成像结果区别明显,证实太赫兹脉冲成像技术能够真实、有效地对真假人民币进行多区域、多维度的准确鉴定。