乡村振兴战略下地方文创产品设计实践研究

目的 从设计学角度探索乡村振兴战略下的文创产品助农模式，深入挖掘、继承和创新优秀的传统乡土文化，将保护、传承和开发利用结合起来，为中华农耕文明赋予新的时代内涵，并应用于平谷区设计实践，助力乡村第一产业和第三产业的发展。方法 依托情感化设计理论，构建文创助农模型，依托北京互联农业果蔬产业创新创业孵化实训基地，借助“以花为媒，营销平谷”的东风，验证模型的可行性。结果 在文创助农模型的基础上，充分挖掘平谷区地方特色文化，结合中国古代哲学系统观“五行”思想，开发五行桃花运势皂，对产品、外观包装及购买交互方式等方面进行深入设计研究，探索了地方特色文创产品设计创新的思路、方法和路径，突出了情感价值提升地方特色文创产品设计的重要作用。结论 文创助农模型能够促进乡村地区农副产品资源的二次利用，提高乡村区域知名度，拉动当地经济增长。     

Combination of dynamic features with a new mask to optimize neural network speech enhancement

Concerning the problem that the Neural Network speech enhancement algorithm cannot fully represent the nonlinear structure of speech due to feature selection,which leads to speech distortion.This paper proposes the combination of dynamic features with a new mask to optimize neural network speech enhancement.First,three features of noisy speech are extracted and spliced to obtain static features.Then,the first and second difference derivatives are obtained to capture the instantaneous signals of speech and fuse them into dynamic features.The combination of dynamic and static features completes internal complementarity of features and reduced speech distortion.Second,in order to enhance the intelligibility and clarity of speech at the same time,an adaptive mask is proposed,which can adjust the energy ratio of speech and noise as well as the ratio of the traditional mask and the square root mask.The Gammatone channel weight is used to modify the mask value in each channel to simulate the human auditory system and further improve the speech intelligibility.Finally,the simulation of multiple voices under different noise backgrounds shows that compared with different literature algorithms,the algorithm has a higher SNR,subjective speech quality and short-term objective intelligibility,which verifies the effectiveness of the algorithm.     

Tibetan Multi-Dialect Speech and Dialect Identity Recognition

Tibetan language has very limited resource for conventional automatic speech recognition so far. It lacks of enough data, sub-word unit, lexicons and word inventories for some dialects. And speech content recognition and dialect classification have been treated as two independent tasks and modeled respectively in most prior works. But the two tasks are highly correlated. In this paper, we present a multi-task WaveNet model to perform simultaneous Tibetan multi-dialect speech recognition and dialect identification. It avoids processing the pronunciation dictionary and word segmentation for new dialects, while, in the meantime, allows training speech recognition and dialect identification in a single model. The experimental results show our method can simultaneously recognize speech content for different Tibetan dialects and identify the dialect with high accuracy using a unified model. The dialect information used in output for training can improve multi-dialect speech recognition accuracy, and the low-resource dialects got higher speech content recognition rate and dialect classification accuracy by multi-dialect and multi-task recognition model than task-specific models.     

一种基于小字典不对等语料的跨语言词嵌入方法

双语词嵌入通常采用从源语言空间到目标语言空间映射,通过源语言映射嵌入到目标语言空间的最小距离线性变换实现跨语言词嵌入。然而大型的平行语料难以获得,词嵌入的准确率难以提高。针对语料数量不对等、双语语料稀缺情况下的跨语言词嵌入问题,该文提出一种基于小字典不对等语料的跨语言词嵌入方法,首先对单语词向量进行归一化,对小字典词对正交最优线性变换求得梯度下降初始值,然后通过对大型源语言(英语)语料进行聚类,借助小字典找到与每一聚类簇相对应的源语言词,取聚类得到的每一簇词向量均值和源语言与目标语言对应的词向量均值,建立新的双语词向量对应关系,将新建立的双语词向量扩展到小字典中,使得小字典得以泛化和扩展。最后,利用泛化扩展后的字典对跨语言词嵌入映射模型进行梯度下降求得最优值。在英语—意大利语、德语和芬兰语上进行了实验验证,实验结果证明该文方法可以在跨语言词嵌入中减少梯度下降迭代次数,减少训练时间,同时在跨语言词嵌入上表现出较好的正确率。     

基于深度分离卷积的情绪识别机器人即时交互研究

情绪识别是人工智能领域的研究热点,人机交互系统若能感知人类的情感行为并能表达情感,将会使机器人与人类的交互更加自然。人类主要通过面部表情、语义语调、肢体语言等几个方面获取情感信息。以拥有高自由度的NAO机器人为应用平台,设计了机器人面部情绪识别和肢体情感表达的人机交互系统。首先,引入深度分离卷积算法对人脸表情(生气、恐惧、伤心、高兴、惊讶和中性)进行特征提取和分类,结果表明通过训练得到的网络模型对FER2013人脸表情测试集的预测正确率可以达到0.711;其次,设计NAO机器人的肢体动作,对6种面部情感做出了分类;最后,对机器人实时表达使用者的情绪状态进行了测试,反馈时间均在2 s内,并对连续10帧预测结果进行了统计分析。     

针对多种处理痕迹的数字语音取证算法

现有的数字语音取证研究主要集中于对单一的某种操作进行检测，无法对不相关的操作进行判断。针对该问题，提出了一种能够同时检测经过变调、低通滤波、高通滤波和加噪这四种操作的数字语音取证方法。首先，计算语音的归一化梅尔频率倒谱系数（MFCC）统计矩特征；然后通过多个二分类器对特征进行训练，并组合投票得到多分类器；最后使用该多分类器对待测语音进行分类。在TIMIT以及UME语音库上的实验结果表明，归一化MFCC统计矩特征在库内实验中均达到了97%以上的检测率，且在对MP3压缩鲁棒性测试的实验中，检测率仍能保持在96%以上。     

基于条件随机场的地质矿产文本分词研究

中文与英文不同,词与词之间没有类似空格的天然分隔符,致使中文分词成为中文信息处理中的难题。地质矿产文本中含有大量未登录地质专业术语,现阶段仍无效果较好的分词方法。本文探讨了一种基于双语料库条件随机场模型的方法对地质矿产文本进行分词,并与通用领域分词方法、单语料库条件随机场模型分词方法进行对比实验。实验表明,本文提出的方法在开放测试下分词效果明显优于其他方法,准确率为94.80%,召回率为92.68%,F-值为93.73%。本文对地质矿产文本进行了中文分词研究,既能够很好地识别未登录地质专业术语,又保证了普通词汇的识别率,为对地质领域的自然语言处理工作奠定了基础。     

消费者情感偏好对运动文胸设计要素的影响

为了解18~45岁女性消费者在购买运动文胸时的情感偏好,以消费者在穿着体验中的评价为依据进行问卷调研,衡量消费者的情感偏好。通过探索性因子分析和验证性因子分析,构建5个一级指标和21个二级指标的消费者情感偏好评价指标模型,采用非线性主成分分析法确定影响消费者情感偏好设计要素的权重值。结果表明:一级指标权重值从大到小依次为面料(0.274)、色彩(0.191)、背部结构(0.188)、肩带形式(0.184)、罩杯形式(0.163),说明面料是消费者购买运动文胸时考虑的主要因素。     

Multiemotional product color design using gray theory and nondominated sorting genetic algorithm-III

When users select products, they consider the emotional experience resulting from the color of the product. However, the emotional demands of users for product color are multidimensional and diverse. It is very important yet difficult to accurately grasp multiemotional image requirements and effectively convert them into design elements. Therefore, multiemotional product color design (MEPCD) has become a very important and challenging research topic. In this article, a novel MEPCD system using gray theory (GT) and nondominated sorting genetic algorithm-III (NSGA-III) is proposed to effectively solve the MEPCD problem. First, the image perception spaces of users, which exist in different emotional dimensions, were collected using factor analysis and the semantic differential technique. Then, GT was used to establish a multidimensional emotional product color image evaluation model. Finally, NSGA-III was used to optimize and design a multiemotional color scheme for a product. Furthermore, according to actual conditions, an MEPCD system was established based on the proposed method. The design case study shows that the method and design system proposed in this article have a certain range of applicability and can effectively improve the practicality of MEPCD.     

DZZ5型自动气象站多媒体故障排查系统的设计与研发

为更有针对性地进行故障排除工作,文章设计研发了一款多媒体软件平台,嵌入细化后的DZZ5型自动气象站各观测要素的故障排查流程,并在相应故障检测节点中添加文字、图片和操作视频。用户可按照流程逐一进行排查操作,或者搜索关键字查看节点内容。同时提供带有关键字查询功能的故障实例库,供基层装备保障业务人员参考。