方言转换系统中的音节切分算法研究

方言转换系统实现了普通话到济南话、沈阳话和西安话的实时语音转换.北方方言之间的差异主要体现在声调上,声调是属于音节的,因此声调转换模式转换是以音节为单位实施的.主要研究了方言转换系统中关键技术:连续语流音节切分算法.提出了一种基于自动机的逐级音节切分算法,分为语段切分、音节切分自动机和切分点自动校正三部分.该算法在误差48ms时,正确率达到72.55%,并成功支持了方言转换中的基频模式转换.     

多生物特征识别平台的设计与实现

针对目前生物特征识别研究大多基于特定特征而难以集成其它特征的现状，提出了整合多种生物特征识别技术的通用解决方案．通过对生物特征识别研究的需求进行分析，抽取了生物特征识别平台的基本逻辑模型．建立了易于扩展、可复用的生物特征识别平台框架THBio，同时在平台中进一步整合了生物特征识别评测厦多生物特征融合的功能，为提高生物特征识别技术的研究水平提供了可能．     

基于FPS200的指纹采集系统与图像增强机制

介绍了基于FPS200芯片的指纹采集系统的设计方案，采用USB方式快速简便地获取指纹原始图像，并能够根据不同采集环境调整芯片参数获得图像最佳清晰度。根据该采集系统输出图像的质量，提出了一套增强算法，通过滤波实现指纹图像的平滑与锐化，计算指纹方向流图并进行背景分割，最后进行二值化处理。算法能够有效减少指纹图像处理的时间消耗，较好地保留了指纹纹线的边缘细节，提高了图像对比度。实验表明，该指纹采集系统与图像增强算法能够获得清晰的指纹细化图，适用于AFIS各种后端处理。     

Affective Image Colorization

Colorization of gray-scale images has attracted many attentions for a long time.An important role of image color is the conveyer of emotions(through color themes).The colorization with an undesired color theme is less useful,even it is semantically correct.However this has been rarely considered.Automatic colorization respecting both the semantics and the emotions is undoubtedly a challenge.In this paper,we propose a complete system for affective image colorization.We only need the user to assist object segmentation along with text labels and an affective word.First,the text labels along with other object characters are jointly used to filter the internet images to give each object a set of semantically correct reference images.Second,we select a set of color themes according to the affective word based on art theories.With these themes,a generic algorithm is used to select the best reference for each object,balancing various requirements.Finally,we propose a hybrid texture synthesis approach for colorization.To the best of our knowledge,it is the first system which is able to efficiently colorize a gray-scale image semantically by an emotionally controllable fashion.Our experiments show the effectiveness of our system,especially the benefit compared with the previous Markov random field(MRF) based method.     

将政治优势和学术优势转化为国防生培养的质量优势——高校高水平国防信息化人才培养模式初探

国防生培养是国家人才战略的重要支撑。文章针对高水平国防信息化人才培养中存在的弱基础与高标准之间的矛盾、易就业与强竞争之间的矛盾以及统一要求与个性发展之间的矛盾,提出"将政治优势和学术优势转化为国防生培养的质量优势"作为工作指导思想,在实践中逐步建立并完善"管理配套,思政到位,学习争优,养训结合,出口把关"五位一体的立体、可持续发展的培养教育模式。     

基于小波图像融合的表情细节合成

表情细节是人脸表情变化时带来的皮肤纹理变化,表情细节合成有助于增强合成表情的真实感.提出了基于小波的图像融合方法,挖掘表情细节的纹理特征本质,并应用到表情细节的合成中,使合成的表情更加真实自然.为了满足表情细节个性化的需求,采用传统的小波变换和双树复小波变换,同时使用不同的融合算子,得到了丰富的表情合成.本方法不仅适用于灰度图像,通过颜色空间的转换还适用于彩色图像.最后还提出了基于聚类和图切割的最优替换区域选取方法,使得合成的表情细节区域与目标图像融为一体.     

基于多模态信息融合的语音意图理解研究

为从语音中获取包括字面含义和说话人情绪状态在内的全面意图信息,提出了一种基于多模态信息融合的语音意图理解方法,并对其中的关键词抽取、命令解析、基于文本/韵律特征的情绪状态检测以及多模态信息融合等关键算法进行了设计.该方法从识别文本和语音信号中抽取不同模态的信息并进行融合,能够有效地从语音中获取丰富的意图信息,有助于建立自然的人机交互环境.     

言语信息处理的进展

该文介绍了言语信息处理的进展,特别提到汉语言语处理的现状。言语信息处理涉及到言语识别、说话人识别、言语合成、言语知觉计算等。带口音和随意发音的言语识别有力的支持了语言学习与口语水平测评等应用;跨信道、环境噪音、多说话人、短语音、时变语音等因素存在的情况下提高识别正确率,是说话人识别的研究热点;言语合成主要关注多语言合成、情感言语合成、可视言语合成等;言语知觉计算开展了言语测听、噪声抑制算法、助听器频响补偿方法、语音信号增强算法等研究。将言语处理技术与语言、网络有效结合,促进了更加和谐的人机言语交互。     

Grading the Severity of Mispronunciations in CAPT Based on Statistical Analysis and Computational Speech Perception

Computer-aided pronunciation training（CAPT） technologies enable the use of automatic speech recognition to detect mispronunciations in second language（L2） learners＇ speech. In order to further facilitate learning, we aim to develop a principle-based method for generating a gradation of the severity of mispronunciations. This paper presents an approach towards gradation that is motivated by auditory perception. We have developed a computational method for generating a perceptual distance（PD） between two spoken phonemes. This is used to compute the auditory confusion of native language（L1）. PD is found to correlate well with the mispronunciations detected in CAPT system for Chinese learners of English,i.e., L1 being Chinese（Mandarin and Cantonese） and L2 being US English. The results show that auditory confusion is indicative of pronunciation confusions in L2 learning. PD can also be used to help us grade the severity of errors（i.e.,mispronunciations that confuse more distant phonemes are more severe） and accordingly prioritize the order of corrective feedback generated for the learners.