Inferring social nature of conversations from words: Experiments on a corpus of everyday telephone conversations

Language is being increasingly harnessed to not only create natural human–machine interfaces but also to infer social behaviors and interactions. In the same vein, we investigate a novel spoken language task, of inferring social relationships in two-party conversations: whether the two parties are related as family, strangers or are involved in business transactions. For our study, we created a corpus of all incoming and outgoing calls from a few homes over the span of a year. On this unique naturalistic corpus of everyday telephone conversations, which is unlike Switchboard or any other public domain corpora, we demonstrate that standard natural language processing techniques can achieve accuracies of about 88%, 82%, 74% and 80% in differentiating business from personal calls, family from non-family calls, familiar from unfamiliar calls and family from other personal calls respectively. Through a series of experiments with our classifiers, we characterize the properties of telephone conversations and find: (a) that 30 words of openings (beginnings) are sufficient to predict business from personal calls, which could potentially be exploited in designing context sensitive interfaces in smart phones; (b) our corpus-based analysis does not support Schegloff and Sack's manual analysis of exemplars in which they conclude that pre-closings differ significantly between business and personal calls – closing fared no better than a random segment; and (c) the distribution of different types of calls are stable over durations as short as 1–2 months. In summary, our results show that social relationships can be inferred automatically in two-party conversations with sufficient accuracy to support practical applications.     

An adaptive neural control scheme for articulatory synthesis of CV sequences

Reproducing the smooth vocal tract trajectories is critical for high quality articulatory speech synthesis. This paper presents an adaptive neural control scheme for such a task using fuzzy logic and neural networks. The control scheme estimates motor commands from trajectories of flesh-points on selected articulators. These motor commands are then used to reproduce the trajectories of the underlying articulators in a 2nd order dynamical system. Initial experiments show that the control scheme is able to manipulate the mass-spring based elastic tract walls in a 2-dimensional articulatory synthesizer and to realize efficient speech motor control. The proposed controller achieves high accuracy during on-line tracking of the lips, the tongue, and the jaw in the simulation of consonant–vowel sequences. It also offers salient features such as generality and adaptability for future developments of control models in articulatory synthesis.     

Language independent search in MediaEval's Spoken Web Search task

In this paper, we describe several approaches to language-independent spoken term detection and compare their performance on a common task, namely “Spoken Web Search”. The goal of this part of the MediaEval initiative is to perform low-resource language-independent audio search using audio as input. The data was taken from “spoken web” material collected over mobile phone connections by IBM India as well as from the LWAZI corpus of African languages. As part of the 2011 and 2012 MediaEval benchmark campaigns, a number of diverse systems were implemented by independent teams, and submitted to the “Spoken Web Search” task. This paper presents the 2011 and 2012 results, and compares the relative merits and weaknesses of approaches developed by participants, providing analysis and directions for future research, in order to improve voice access to spoken information in low resource settings.     

合成氢化松香乙酯的新工艺研究

以DRC为催化剂,在无溶剂条件下,通过氢化松香与乙醇的直接酯化反应合成氢化松香乙酯。探索了反应温度、催化剂用量、反应时间、物料配比等因素对反应酯化率的影响,确定最佳反应条件为:反应温度180℃,催化剂用量为原料氢化松香质量的6%,反应时间6h,醇与酸的摩尔比为3∶1。在最佳条件下酯化率达92.2%。还探讨了用阴离子交换树脂柱层析分离纯化氢化松香乙酯粗产物的方法。此外,利用红外光谱对氢化松香乙酯精制产物进行了表征;用GC-MS分别对氢化松香乙酯粗产物及其精制产物进行了定性和定量分析,比较了柱层析前后化学组成的变化。     

四丁基脲的合成方法

四丁基脲(简称TBU)是一种用途很广的有机合成中间体,对其制备方法的研究具有重要的现实意义。笔者系统介绍了合成四丁基脲的方法,归纳分析目前生产四丁基脲的方法,比较各种方法的优缺点,并对今后的研究方向进行了展望。     

聚己二酸1,2-环己二醇酯的合成

采用正交实验方法,分别以钛酸四丁酯和对甲苯磺酸为催化剂,合成了聚己二酸1,2 环己二醇酯,对其合成工艺条件进行了研究,得出了最佳工艺条件。并以所得聚酯合成了具有透明度高、硬度大、耐磨、玻璃化温度高等优异性能的聚氨酯材料。     

TiB2的SHS合成过程理论分析

在ＴｉＢ２陶瓷材料的自蔓延高温合成（简称ＳＨＳ）过程中，通过改变原料的起始温度，稀释剂的含量和原始颗粒的尺寸等都可以调节合成过程的绝热温度，产物中熔融相的含量，以及燃烧波蔓延的速度，人而最终影响合成产物的结构和性质。本文对上述各种关系进行了理论计算和分析，其结果对实际合成与制备过程将有着重要的指导作用。     

莫达非尼的绿色化学合成

采用[bm im]BF4离子液体作为反应溶剂,以二苯甲硫醇为原料,经醚化、氨解、氧化得到新型提神醒脑药物莫达非尼。讨论了不同的氯乙酸酯和反应温度对醚化反应收率的影响,讨论了不同的二苯甲硫乙酸酯对氨解反应收率的影响,及离子液体的回收使用。研究表明,采用氯乙酸甲酯作为醚化试剂,反应时间4 h,反应温度100℃,二苯甲硫醇∶氯乙酸甲酯=1∶1.5(摩尔比),室温下氨解反应20 h,二苯甲硫乙酰胺收率76%;采用过氧化氢作为氧化试剂,反应时间3 h,反应温度60℃,过氧化氢∶二苯甲硫乙酰胺=1∶1(摩尔比),莫达非尼收率79%,反应总收率可达48%。     

New perfectly difunctional organolithium initiators for block copolymer synthesis: 2. Difunctional polymers of dienes and of their triblocks copolymers with styrene

New organodilithium initiators were prepared in a hydrocarbon solvent in the absence of any polar additive. Although these initiators are insoluble when they are synthesized, they may be easily purified and reacted with dienes to give perfectly telechelic polydienes having unimodal distributions and low dispersity. A good agreement between experimental and theoretical molecular weights was observed. The polymer microstructures were similar to those of polymers initiated by butyllithium in the same solvent. Triblock thermoplastic elastomers were also prepared, the characteristics of which are given. The mechanical properties of a S.B.S. sample support also the claim of a good initiating ability and difunctionality of these initiators.     

美国能源部的浆态床F－T合成技术

浆态床Ｆ－Ｔ合成技术是美国能源部Ｆ－Ｔ合成技术的主要开发项目。本文就浆态相Ｆ－Ｔ合成催化剂的开发、中试示范实验和浆态反应器的化工基础研究作一扼要的介绍。