智能聊天机器人在C语言程序设计教学中的应用

随着人工智能技术的迅猛发展,聊天机器人也得到长足发展。将聊天机器人应用到教学中,可以解放教学中相 对固化、重复的密集型任务或流程所需的人力,聊天机器人以客户为中心的理念与职业教育以学生为中心的理念不谋而合。 探讨了聊天机器人导学方法的内涵,并尝试将在线评测OJ 平台与聊天机器人相结合,在C语言教学和竞赛辅导中应用,总结 和分析聊天机器人对C语言教学产生的积极作用和教学场景,积极探索基于AI 的智能教学模式。     

检索式聊天机器人技术综述

随着自然语言处理技术的飞速发展以及互联网上对话语料的不断积累,闲聊导向对话系统(简称聊天机器人)取得了令人瞩目的进展,受到了学术界的广泛关注,并在产业界进行了初步的尝试.当前,聊天机器人分为检索式聊天机器人和生成式聊天机器人,而检索式聊天机器人由于其生成的回复流畅且计算资源消耗小,仍然是目前工业界聊天机器人的主要实现手段.文中首先简要介绍了检索式聊天机器人的研究背景、基本架构以及组成模块,重点阐述了回复选择模块的约束要求和相关数据集;然后,针对检索式聊天机器人中最为核心的回复选择技术,进行了深入分析与详细梳理.文中将近年来经典的回复选择技术归纳为如下4类:基于统计模型的方法、基于表示的神经网络模型的方法、基于交互的神经网络模型的方法以及基于预训练技术的方法,并指出了这4类方法的优点和不足.在此基础上,分析了目前检索式聊天机器人技术研究所面临的问题,并对其未来的发展趋势进行了展望.     

抢入口还早，先把聊天机器人做好再说吧

近日，Kik这款聊天机器人，它号称吸引了40％的美国青少年成为其活跃用户。Kik之所以受欢迎，得益于其创始人泰德·利文斯顿提出的新颖概念——“人们可以通过机器人直接与品牌对话”。联想到之前的微软小冰，也是一个在国内引起了巨大关注的聊天机器人，它甚至成功吸引到了雷军、周鸿神等互联网大佬的注意力。为什么这么多巨头迷恋于聊天机器人？     

聊天机器人的分类标准和评估标准综述

近年来,人工智能和大数据技术的发展极大地推动了聊天机器人产业的发展.如今,聊天机器人种类众多,但质量参差不齐,对其进行评估成为当下的重要问题之一.本文首先通过功能和技术实现方式方面的分析,对当前的聊天机器人进行了归纳分类.然后从多方面对聊天机器人的评估方式进行了系统的整理与总结,并详细介绍分析了其中各种评估指标.最后探...     

最新MSN聊天机器人大揭秘

如果你想在MSN中查询天气预报、列车时间表、星座、歌曲等信息，可以去找聊天机器人。这些小精灵有的会说中国话，有的则只会英文，它们都是某方面的专家权威，可以通过聊天的方式回答你的问题！由于使用者众多，目前新用户免费添加的机器人账号非常稀少，有的机器人（例如小布）则干脆改成收费的了，缴了钱才可以使用。下面我们就来走近MSN聊天机器人，看看目前还有哪些机器人可以使用！     

最新MSN聊天机器人大揭秘

如果你想在MSN中查询天气预报、列车时刻表、星座、歌曲等信息,可以去找聊天机器人。这些小精灵有的会说中国话,有的则只会英文,它们都是某方面的专家权威,可以通过聊天的方式回答你的问题!由于使用者众多,目前新用户能免费添加的机器人帐号非常稀少,有的机器人(例如小布)则干脆改成收费的了,缴了钱才可以使用。下面我们就来走近MSN聊天机器人,看看目前还有哪些机器人可以使用!     

分布式虚拟环境中的聊天机器人的研究

该文探索了通过自然语言界面从基于Web的应用中获取知识的一种方法。介绍了一些著名聊天机器人程序着重给出了基于AIML的聊天机器人A.L.I.C.E的运行机制,并分析了其适合于分布式应用的特点。通过对其进行改进将其结合进分布式虚拟环境中,构造了一个基于Web的分布式虚拟环境中的聊天机器人。     

“机器人”受聘当员工方正科技将服务推向用户桌面

近日,一名虚拟的“员工”加入到方正科技客服的行列中,引起了很多网友的关注。原来,任何人只需添加beida_fangzheng@hotmail．com为MSN好友,就可与方正科技客服机器人开始聊天,获取电脑使用和维修问题的解决方案,还能得到软硬件知识的培训等服务。     

和聊天机器人过招

用MSNMessenger、QQ等即时通讯软件和朋友聊天也许是你经常干的事,但如果正和你聊天的朋友是一个机器人,那会是怎样一种感觉呢?这里就带你会会几位聊天机器人——小I、小布&珊瑚虫和EncartaInstantAnswers(电子百科全书)。     

基于深度学习的个性化聊天机器人研究

为了对传统的聊天机器人局限性进行改进,增强其回复时的个性化和多样化,并使其具有一定的准确性,研究改进了一种基于深度学习Seq2Seq模型的对话系统。对传统的编码器-解码器(Encoder-Decoder)模型进行了研究,在原有模型的基础上使用了深度LSTM结构并且加入注意力机制使其能更好地适应不同长度的问句。在解码过程中,将原有模型的贪心算法改为了Beam Search算法。在训练过程中,利用了多次训练的方法,训练出模拟电视剧角色的聊天机器人,为聊天机器人赋予一个特定的身份。通过使用两种自动评估指标BLEUs和Distinct-n去测试聊天机器人,并使用一些问句测试聊天机器人的反应,最终实验结果表明新模型与原有的模型相比,两种指标都取得了较好的效果,并且输出句子的合理性以及回复质量也有明显的提高。     

Spontaneous Speech Parsing in Travel Information Inquiring and Booking Systems

Grammar-based parsing is a prevalent method for natural language understanding(NLU)and has been introduced into dialogue systems for spoken language processing (SLP).A robust parsing scheme is proposed in this paper to overcome the notorious phenomena,such as garbage,ellipsis,word disordering,fragment ,and ill-form,which frequently occur in splien utterances,Keyword categories are used as terminal symbols,and the definition of grammar is extended by introducing three new rule types,by-passing,up-messing and overcrossing,in addition to the general rules called up-tying in this paper,and the use of semantic items simplifies the semantics extraction.The corresponding parser marionette,which is essentially a partial chart parser,is enhanced to parse the semantic grammar.The robust parsing scheme integrating the above methods has been adopted in an air traveling information service system called EasyFlight,and has achieved a high performance when used for parsing spontaneous speeches.     

对话管理中基于槽特征有限状态自动机的方法研究

对话系统的研究已经成为人机交互技术发展的新热点。而对话管理则是其中最重要的组成部分．该文在当前对话管理的各种实现方法的基础上，提出了一种基于槽特征的自动机设计方法，其中应用了状态压缩和状态集、动作集的子空间划分。并着重以确认过程为例，阐述了确认策略控制函数及其对对话过程的影响．文中还提出了一种树形的意图分层结构，并将这种分层结构应用于主题检测与主题切换，成功解决了多主题对话系统的主题切换问题．最后，实验表明该文提出的设计方案在策略控制、主题检测与主题切换等方面具有较好性能，同时也具有一定扩展性．     

口语对话系统的POMDP模型及求解

许多口语对话系统已进入实用阶段，但一直没有很好的对话管理模型，把对话管理看做随机优化问题，用马尔科夫决策过程（MDP）来建模是最近出现的方向，但是对话状态的不确定性使MDP不能很好地反映对话模型，提出了一种新的基于部分可观察MDP（POMDP）的口语对话系统模型，用部分可观察特性来处理不确定问题，由于精确求解算法的局限性，考察了许多启发式近似算法在该模型中的话用性，并改进了部分算法，如对于格点近似算法，提出了两种基于模拟点的格点选择方法。     

The Syrinx Spoken Language System

This paper describes the Syrinx Spoken Language System (Sylan), an automated dialogue system that is fully integrated with the Syrinx Large Vocabulary Speech Recogniser (Sycon) into the Syrinx SpeechMaster platform. This platform combines speech recognition, natural language processing, dialogue management, telephony and database integration into a robust and flexible Voice User Interface that permits the deployment of natural language dialogue systems in automated call centres. We first describe the architecture of Sylan which, being modular, allows us to build a system whose domain-independent components are reusable from application to application. We then present those components from the point of view of application developers, describing the data structures used by the system and the utilities to build them. The two prototypes that have already been developed using Sylan are briefly presented, and we conclude by drawing the lessons learned along the way and pointing to further research directions.     

基于两阶段分类的口语理解方法

口语理解是实现口语对话系统的关键技术之一.它主要面临两方面的挑战:1)稳健性,因为输入语句往往是病态的;2)可移植性,即口语理解单元应能够快速移植到新的领域和语言.提出了一种新的基于两阶段分类的口语理解方法:第1阶段为主题分类,用来识别用户输入语句的主题;第2阶段为主题相关的语义槽分类,根据识别的主题抽取相应的语义槽/值对.该方法能对用户输入语句进行深层理解,同时也能保持稳健性.它基本上是数据驱动的,而且训练数据的标记也比较容易,可方便地移植到新的领域和语言.实验分别在汉语交通查询领域和英语DARPA Communicator领域进行,结果表明了该方法的有效性.     

User Modeling in Spoken Dialogue Systems to Generate Flexible Guidance

We address the issue of appropriate user modeling to generate cooperative responses to users in spoken dialogue systems. Unlike previous studies that have focused on a user’s knowledge, we propose more generalized modeling. We specifically set up three dimensions for user models: the skill level in use of the system, the knowledge level about the target domain, and the degree of urgency. Moreover, the models are automatically derived by decision tree learning using actual dialogue data collected by the system. We obtained reasonable accuracy in classification for all dimensions. Dialogue strategies based on user modeling were implemented on the Kyoto City Bus Information System that was developed at our laboratory. Experimental evaluations revealed that the cooperative responses adapted to each subject type served as good guides for novices without increasing the duration dialogue lasted for skilled users.     

Users' Conceptions of Voice-Operated Information Services

When users interact with a voice-operated service, they bring along their habits as well as their expectations from experience with human-human dialogues, with the domain, and with other systems and services. In addition, users' expectations are further shaped while using a system. The present study explores the extent to which user-system interaction, and in particular difficulties in the interaction, are affected by users' expectations and (mis)conceptions of the service, and how these expectations evolve during use. In an exploratory study, twenty subjects queried two different train travel information services. A semi-structured interview was held on subjects' dialogues with the systems, by replaying the recordings together with the subjects. In interacting with voice-operated services, users appear to draw from various sources of experience. Users' misconceptions and misunderstandings of the system lead to various problems in interaction, such as undesired travel suggestions and irritation. The implications for the design of voice-operated services are discussed.     

A robust system for human-machine dialogue in telephony-based applications

This paper presents a real-time system for human-machine spoken dialogue on the telephone in task-oriented domains. The system has been tested in a large trial with inexperienced users and it has proved robust enough to allow spontaneous interactions even for people with poor recognition performance. The robust behaviour of the system has been achieved by combining the use of specific language models during the recognition phase of analysis, the tolerance toward spontaneous speech phenomena, the activity of a robust parser, and the use of pragmatic-based dialogue knowledge. This integration of the different modules allows the system to deal with partial or total breakdowns at other levels of analysis. We report the field trial data of the system with respect to speech recognition metrics of word accuracy and sentence understanding rate, time-to-completion, time-to-acquisition of crucial parameters, and degree of success of the interactions in providing the speakers with the information they required. The evaluation data show that most of the subjects were able to interact fruitfully with the system. These results suggest that the design choices made to achieve robust behaviour are a promising way to create usable spoken language telephone systems.