元音差异对声调感知范畴的影响

0引言汉语是一种声调语言[1]。元音作为声调的承载体,必然对声调产生重要的影响。以往的研究[2,3]主要集中在元音对于声调基频走势以及声调识别的影响上,而针对声调的感知范畴边界的影响却相对较少。本文选取了普通话声调四声齐全的三个单元音[a,i,u]作为原始材料,采用"基音同步叠加(PSOLA)"方法对原始语音进行修改合成,并使     

双耳分听汉语普通话声调研究

系统地探讨与研究了以汉语为母语的右利手被试者对汉语普通话声调感知的偏侧优势。选取40个常用的汉语普通话单音节词作为实验材料,在合适的反应时间和信噪比下采用双耳分听范式进行声调辨别听觉感知实验。实验要求被试者从同时、分别播放到左右耳的不同声调中选出一个最清楚听到的声调,而不考虑所选的声调来自左耳还是右耳。30位听力正常的右利手被试者参与了此项实验。实验结果表明,在本研究设定的双耳分听实验条件下,汉语为母语的右利手被试者对汉语普通话声调的感知存在显著的右耳(大脑左半球)优势,且对四个声调的感知具有相同的偏侧优势;左、右耳对四个声调间感知差异的趋势基本一致,且对3声的感知显著较其余声调差。     

在华巴斯坦留学生单字调的声学实验和统计调查分析

本文从纵向和横向的角度考察学生在不同阶段对汉语拼音声调的学习情况,对在华学习汉语的8名巴基斯坦学生进行调查分析,利用声学实验和数据统计分析的方法来考察了他们的声调特征。从历时的角度考察留学生对声调的习得程度,并分析其声调偏误。实验分析得出巴基斯坦学生的上声调最标准,其次是阳平。阴平和去声偏误较大。     

新疆民族大学生汉语声调感知与发声偏误关系

0引言众多学者已对无声调母语学习者的汉语声调感知偏误、范畴感知、发声偏误等方面进行了实验和分析[1][2]。一般研究中都认为声调感知和发声具有相互促进的作用,并且发声是基于感知的。Yang和Ankenmann(2007)对美国的汉语学习者的声调感知和发声进行测试,发现被试的感知受声调类型影响,而发声则没有显著差别[3]。Bent(2005)对20位英语     

不同水平的普通话学习者单字调声调感知研究

首先采用实验语音学的理论和方法进行比较分析,进一步了解普通话学习者声调学习的情况,通过定量研究的方法,对两种不同水平(高级水平和初级水平)学习者的声调感知进行声学分析并对学习普通话过程中的语调掌握状况展开探讨。考察了20名不同水平学习者对普通话声调学习的感知情况。按学习者对汉语9个单元音的4个声调感知和12个复合元音的4个声调的单字调辨认,以及阳平-上声的区分实验数据,统计学习者的辨认准确率、各调类的偏误率和反应时间,最后利用SPSS数据分析软件从统计的角度进行了辨认准确率和反应时间的相关性分析,分别对声调感知的准确率和反应时间的显著性差异进行检验。     

基于声学特征的母语非汉语者声调研究

从提高满足少数民族普通话高自然度语音合成与高精度语音识别的实际应用需求出发,首次从实验语音学的角度对初级、中级和高级阶段的50名维吾尔族汉语学习者与10名母语为汉语普通话的说话人声调的一阶差分与时长以及相似度进行对比,并对其声调的一阶差分模式、声调时长等韵律参数进行了实验分析,得出维吾尔族学生对汉语声调的偏误情况以及与中国少数民族汉语水平等级考试(Master of Human Kinetics, MHK)成绩的关系。通过实验结果可以发现,三组维吾尔族人学习普通话的声调都有困难。两种语言的音系,语调和重音等特性影响了第二语言中的声调特性。归纳了维吾尔族学习者声调的基本声学特征,总结出了一些重要的规则和结论;为解决给汉语语音处理带来的困难,尤其是少数民族汉语的语音合成和语音识别方面的声调问题,提供了重要的参考依据。     

数码"单反"常见问题解答

随着数码单反相机的日益普及,随之带来的问题和疑问也越来越多.特别是最近一段时间伴随着佳能EOS300D、EOS20D的畅销,在使用过程中大量出现的诸如焦点偏移、图像锐度不高等问题,相继成为广大影友中广为争议的焦点,各种说法莫衷一是.有些影友甚至对数码单反相机提出了质疑,认为数码单反相机的影像质量甚至比不上民用数码相机的影像品质.到底这些问题是如何产生的?结合佳能公司的<佳能数码单反常见问题答集>和广大影友在数码单反相机在使用中经常遇到的一些疑问,笔者编辑整理出这篇数码单反常见问题解答,或许会对广大影友具有一定的参考意义,具体内容如下:     

支持矢量机的汉语声调识别

提出了一种支持矢量机的汉语声调识别新方法。论文首先在基频和对数能量的基础上,建立了一个适合于支持矢量机分类的等维声调特征。然后对支持矢量机的多分类策略和不同核函数对声调识别的影响进行了实验研究。与BP神经网络相比,支持矢量机具有更高的识别率和更强的推广能力。     

介绍几款全音域扬声器

音响系统中的扬声器除了有高音、中音、低音、超高音、超低音之分外,还有全音域的,又称全频扬声器单元。全音域扬声器单元盛行于20世纪的40-60年代。当年全音域单元用在收音机、剧院、电影院中,或公共场所作广播用。制造全音域单元较著名的有美国的“西电”、英国、德国、日本等,国产的飞乐牌单元也颇有口碑。     

一种新的汉语连续语音声调评测算法

提出一种新的连续语音的声调评测算法,该算法可应用于计算机辅助语言学习系统和普通话水平测试中的声调评测。考虑到连续语音声调受上下文之间的相互影响,采用三音节单元建立高斯混合模型(Gaussian Mixture Model, GMM),三音节中辅音部分用Spline插值法拟合声调曲线来反映音节间基音频率的转移信息,并利用Fujisaki模型去除语句的语调和说话人个性特征,只对基频曲线中的声调特征建模。实验结果显示,相比于传统方法,采用三音节Spline插值和Fujisaki改进特征的方法使得机器与人工打分的相似度在测试集中分别提高了8.75%和14.09%。     

Tone recognition for continuous mandarin speech with limited training data using selected context‐dependent hidden markov models

Abstract

Mandarin Chinese is a tonal language, in which every syllable is assigned a tone that has a lexical meaning. Therefore tone recognition is very important for Mandarin speech. This paper presents a method for continuous speech tone recognition. Context‐dependent discrete hidden Markov models (HMM's) are used taking into account the tones of the syllables on both sides, and special efforts were made in selecting the minimum number of key context‐dependent models considering the characteristics of the tones. The results indicate that a total of 23 context‐dependent models have very good potential to describe the complicated tone behavior for all 175 possible tone concatenation conditions in continuous speech, such that the required training data can be reduced to a minimum and the recognition process can be simplified significantly. The best achievable recognition rate is 83.55 %.     

Third-order parametric array generated by distantly spaced primary ultrasonic tones

Traditional parametric arrays are produced by a second-order nonlinear interaction between two primary ultrasonic tones that are close in frequency, resulting in a difference tone that is in the audio band. This article presents a parametric array produced by a third-order nonlinear interaction between two primary ultrasonic tones that are distantly spaced in frequency such that one tone is approximately the second harmonic of the other. The result is a third-order lower intermodulation (IM3) tone in the audio band with greater directivity and lower side lobe amplitude than comparable second-order fields. Measurements are presented that compare the directivity of 1-, 2-, and 4-kHz difference tones to that of 1-, 2-, and 4-kHz IM3 lower tones. Furthermore, a cascaded second-order approach for N-element transducer arrays is used to model third-order scattering with good agreement between measurement and theory.     

Text‐independent speaker identification via LPC and tone structure of mandarin speech

Abstract

By taking advantage of four‐tone structure in the pitch contour of Mandarin speech, we described text‐independent speaker identification using orthogonal pitch parameters. Slopes, mean and duration of the pitch contours of words in an utterance are taken as recognition features. An identification rate of 85% is achieved by using the parameters of pitch contour only. When incorporating parameters of pitch contour with the parameter of vocal tract, this system outperforms that using parameters of vocal tract or pitch contour only. A recognition rate of 99.7% is reached in such a system.     

English to Tamil machine translation system using universal networking language

This paper proposes English to Tamil machine translation system, using the universal networking language (UNL) as the intermediate representation. The UNL approach is a hybrid approach of the rule and knowledge-based approaches to machine translation. UNL is a declarative formal language, specifically designed to represent semantic data extracted from a natural language text. The input English sentence is converted to UNL (enconversion), which is then converted to a Tamil sentence (deconversion) by ensuring that the meaning of the input sentence is preserved. The representation of UNL was modified to suit the translation process. A new sentence formation algorithm was also proposed to rearrange the translated Tamil words to sentences. The translation system was evaluated using bilingual evaluation understudy (BLEU) score. A BLEU score of 0.581 was achieved, which is an indication that most of the information in the input sentence is retained in the translated sentence. The scores obtained using the UNL based approach were compared with existing approaches to translation, and it can be concluded that the UNL is a more suited approach to machine translation.     

句子学习过程中的眼动特征

为了探讨重复学习对于汉语句子理解的作用,采用眼动仪记录10名研究生被试连续5次阅读20个句子时的眼动模式.研究结果表明：①随着阅读次数的增加,句子阅读时间依次缩短;注视点数目和回视次数逐渐减少;注视点的平均持续时间波动较小;平均眼跳距离逐渐加长;瞳孔尺寸逐渐变大.②其中瞳孔尺寸的变化模式揭示了句子学习过程中可能存在作业难度和认知负荷之间的分离--随着阅读次数的增加,作业难度降低,而认知负荷逐渐升高.③多种指标表明句子学习过程中知觉广度随阅读次数增加而加大.     

民用飞机噪声适航审定中伪纯音影响的去除方法

在民用飞机噪声适航合格审中计算有效感觉噪声级时,通过引入纯音修正因子来考虑噪声频谱不规则性对人主观感觉的影响,但布置在地面上的传声器测量的噪声频谱中含有地面影响导致的伪纯音,使得纯音修正因子可能被高估,需要加以识别并去除。该文提出了一种识别和去除地面影响引入的伪纯音对纯音修正因子计算影响的飞行试验方法和分析方法。在适航噪声测量点旁布置倒置传声器,得到飞机直达噪声,可靠地识别实测适航噪声频谱中的伪纯音,基于"CCAR-36部"及其附件中方法的改进方法,去除伪纯音对纯音修正因子计算的影响。通过某型民机噪声适航审定飞行试验对该方法进行了验证,结果表明该方法满足"CCAR-36部"等规章要求,易于试验和分析实现,能准确去除由地面影响引入的伪纯音影响,提高了有效感觉噪声级的计算准确度。     

Proximity Analysis of Pitch Perception of Complex Tones in Endless Scale

Behaviormetrika - Experiments were carried out on the pitch of two groups of computer-generated complex tones. The sequence of the ten complex tones in group A are perceived as an endless scale...     

利用五度字调模型实现普通话到兰州方言的转换

方言语音的转换对于实现个性化的汉语语音合成系统具有重要的意义。为了实现普通话到兰州方言的转换,论文利用《方言调查字表》建立了兰州方言的文本语料库,录制了普通话和兰州方言平行的语音语料库。利用五度字调模型建立了普通话和兰州方言的基频模型,利用统计方法建立了时长转换模型和停顿时长转换模型。在转换时,通过利用STRAIGHT算法修改普通话语音实现普通话到兰州方言的转换。对转换结果的MOS评测表明,转换后的单字平均MOS得分4.17,双字平均MOS得分为4.22,语句的平均MOS得分为3.55。     

Sentence Similarity Measurement with Convolutional Neural Networks Using Semantic and Syntactic Features

Calculating the semantic similarity of two sentences is an extremely challenging problem. We propose a solution based on convolutional neural networks (CNN) using semantic and syntactic features of sentences. The similarity score between two sentences is computed as follows. First, given a sentence, two matrices are constructed accordingly, which are called the syntax model input matrix and the semantic model input matrix; one records some syntax features, and the other records some semantic features. By experimenting with different arrangements of representing the syntactic and semantic features of the sentences in the matrices, we adopt the most effective way of constructing the matrices. Second, these two matrices are given to two neural networks, which are called the sentence model and the semantic model, respectively. The convolution process of the neural networks of the two models is carried out in multiple perspectives. The outputs of the two models are combined as a vector, which is the representation of the sentence. Third, given the representation vectors of two sentences, the similarity score of these representations is computed by a layer in the CNN. Experiment results show that our algorithm (SSCNN) surpasses the performance MPCPP, which noticeably the best recent work of using CNN for sentence similarity computation. Comparing with MPCNN, the convolution computation in SSCNN is considerably simpler. Based on the results of this work, we suggest that by further utilization of semantic and syntactic features, the performance of sentence similarity measurements has considerable potentials to be improved in the future.