近程反导舰炮武器系统闭环校射研究

为了满足抗击反舰导弹的要求,近程反导舰炮武器系统必须大大提高射击精度,闭环校射是提高射击精度的有效途径。为了保证闭环校射的效果,必须获得精确的脱靶量测量值,建立有效的脱靶量预测模型。研究了适合近程反导舰炮武器系统的脱靶量测量方法。从闭环校射角度出发对射击误差进行了分类,利用tf时刻脱靶量将机动误差和外部误差引起的脱靶量进行了分离,利用近程反导舰炮武器的弹道特性,从测量获得的脱靶量中求出tf时刻脱靶量。最后,利用最小二乘滤波建立了脱靶量预测模型并进行了仿真计算。     

Simultaneous gesture segmentation and recognition based on forward spotting accumulative HMMs

Existing gesture segmentations use the backward spotting scheme that first detects the end point, then traces back to the start point and sends the extracted gesture segment to the hidden Markov model (HMM) for gesture recognition. This makes an inevitable time delay between the gesture segmentation and recognition and is not appropriate for continuous gesture recognition. To solve this problem, we propose a forward spotting scheme that executes gesture segmentation and recognition simultaneously. The start and end points of gestures are determined by zero crossing from negative to positive (or from positive to negative) of a competitive differential observation probability that is defined by the difference of observation probability between the maximal gesture and the non-gesture. We also propose the sliding window and accumulative HMMs. The former is used to alleviate the effect of incomplete feature extraction on the observation probability and the latter improves the gesture recognition rate greatly by accepting all accumulated gesture segments between the start and end points and deciding the gesture type by a majority vote of all intermediate recognition results. We use the predetermined association mapping to determine the 3D articulation data, which reduces the feature extraction time greatly. We apply the proposed simultaneous gesture segmentation and recognition method to recognize the upper-body gestures for controlling the curtains and lights in a smart home environment. Experimental results show that the proposed method has a good recognition rate of 95.42% for continuously changing gestures.     

广播新闻语音的关键词检测系统

提出了一种两阶段的关键词检测策略，关键词表可即时配置、即时使用。与以往不同的是，解码是在整个声学空间上进行的，而不仅仅是关键词所构成的声学空间。首先，利用维特比解码得到最优候选的音素序列。然后，通过关键词列表，可以产生候选的关键词。最后，采用了基于声学模型的置信度与基于网格的置信度相结合的方法来降低虚警。实验证明，新的框架下关键词检测的性能得到了显著的提高。     

一种新型测距仪的研制

介绍了一种在中，小范围内，采用激光定位，超声测距的新型测量仪器，该仪器以单片微处理器为核心，对不同的测量距离，采用不同频率的超声波，结合信号处理方法，从而实现０．６～１４ｍ范围内高精度实时测量目标距离，其测量相对误差优于１％。     

HMM关键词检出系统专

关键词检出(keywordspottin)g也称词检出(wordspottin)g,是近年来语音识别中颇受重视的研究领域,可广泛应用于电话的自动接听和对话监听、语音的录入和检索等方面。文中首先介绍了关键词检出的HMM方案及其研究成果,并对其进行了仿真实验,最后指出了关键词检出尚待解决的一些问题及研究方向。     

A Multi‐Strategic Concept‐Spotting Approach for Robust Understanding of Spoken Korean

We propose a multi‐strategic concept‐spotting approach for robust spoken language understanding of conversational Korean in a hostile recognition environment such as in‐car navigation and telebanking services. Our concept‐spotting method adopts a partial semantic understanding strategy within a given specific domain since the method tries to directly extract pre‐defined meaning representation slot values from spoken language inputs. In spite of partial understanding, we can efficiently acquire the necessary information to compose interesting applications because the meaning representation slots are properly designed for specific domain‐oriented understanding tasks. We also propose a multi‐strategic method based on this concept‐spotting approach such as a voting method. We present experiments conducted to verify the feasibility of these methods using a variety of spoken Korean data.     

Issue spotting in CHASER

For any system that uses previous experience to solve problems in new situations, it is necessary to identify the features in the situation that should match features in the previous cases through some process ofsituation analysis. In this paper, we examine this problem in the legal domain, where lawyers know it asissue spotting. In particular, we present an implementation of issue spotting in CHASER, a legal reasoning system that works in the domain of tort law.This approach is a compromise between generality and efficiency, and is applicable to a range of problems and domains besides legal reasoning. In particular, it presents a principled way to use multiple cases for a single problem by exploiting the inherent structure present in many domains.This work has been supported in part by the National Science Foundation, grant IRI-9110961.     

用普通建筑沥青制备的粉状解卡剂JQG

用10号建筑沥青，石灰，有机土，油酸，渗透剂，抗温乳化剂制成了粉状解卡剂JQG。介绍了制造工艺和室内制品配方。以常用的用氧化沥青制成的粉状解卡剂CPF为对比剂，对JQG的性能进行了0室内评价，解卡剂JQG（解卡浸泡液）的细度，破乳电压，塑性粘度，屈服值，滤失量，硬沉淀，解卡性能全部符合行业标准；在150℃，16h静置处理中JQG解卡浸泡液中浸泡28h后降为零，而在CPF解卡浸泡液中需浸泡44h才降为零；JQG解卡浸泡液能浸透3mm厚的泥浆泥饼，使泥饼分裂为小碎块，烘干后变疏松而大面积脱落。CPF解卡浸泡液对泥饼的渗透深度只有1mm，泥饼分裂为大块。烘干后不脱落，JQG的解卡性能优于CPF。     

1-MCP抑制香蕉货架期衰老斑点的研究

以广东高州香蕉为实验材料,研究了1-甲基环丙烯对成熟香蕉老化斑点产生的影响。结果表明:即使催熟至批发成熟度(果皮3/4面积变黄)和零售成熟度(果皮转黄)的香蕉,0.5和1.0μL/L的1-MCP处理,仍可显著延迟果皮衰老斑点的产生,延长货架寿命;1-MCP处理延迟了批发成熟度香蕉果皮褪绿和果肉淀粉降解,对于抑制2种成熟度的香蕉货架后期组织崩溃水渍症状的出现,也具有良好效果,处理效果以批发成熟度更好;2个1-MCP剂量间无显著差异。     

Improving the performance of keyword spotting system for children's speech through prosody modification

Searching for words of interest from a speech sequence is referred to as keyword spotting (KWS). A myriad of techniques have been proposed over the years for effectively spotting keywords from adults' speech. However, not much work has been reported on KWS for children's speech. The speech data for adult and child speakers differs significantly due to physiological differences between the two groups of speakers. Consequently, the performance of a KWS system trained on adults' speech degrades severely when used by children due to the acoustic mismatch. In this paper, we present our efforts towards improving the performance of keyword spotting systems for children's speech under limited data scenario. In this regard, we have explored prosody modification in order to reduce the acoustic mismatch resulting from the differences in pitch and speaking-rate. The prosody modification technique explored in this paper is the one based on glottal closure instant (GCI) events. The approach based on zero-frequency filtering (ZFF) is used to compute the GCI locations. Further, we have presented two different ways for effectively applying prosody modification. In the first case, prosody modification is applied to the children's speech test set prior to the decoding step in order to improve the recognition performance. Alternatively, we have also applied prosody modification to the training data from adult speakers. The original as well as the prosody modified adults' speech data are then augmented together before learning the statistical parameters of the KWS system. The experimental evaluations presented in this paper show that, significantly improved performances for children's speech are obtained by both of the aforementioned approaches of applying prosody modification. Prosody-modification-based data augmentation helps in improving the performance with respect to adults' speech as well.