Adding extra inputoutput modalities to a spoken dialogue system

Adding extra inputoutput modalities to a spoken dialogue system
Adding extra inputoutput modalities to a spoken dialogue system

Adding extra input/output modalities to a spoken dialogue system Janienke STURM, Fusi WANG, Bert CRANEN

A2RT, Dept. Language and Speech, Nijmegen University

Erasmusplein 1

6525 HT Nijmegen, The Netherlands

{janienke.sturm | f.wang | b.cranen}@let.kun.nl

Abstract

This paper describes a prototype of a multi-modal railway information system that was built by extending an existing speech-only system. The purpose of the extensions is to alleviate a number of shortcomings of speech-only interfaces.

1Introduction

For a long time, speech has been the only mo-dality for input and output in telephone-based in-formation systems. Speech is often considered to be the most natural form of input for such sys-tems, since people have always used speech as the primary means of communication. More-over, to use a speech-only system a simple tele-phone suffices and no additional devices are re-quired. Obviously, in situations where both hands and eyes are busy, speech is definitely preferable over other modalities like pen/mouse. However, speech-only interfaces have also shown a number of shortcomings that result in less effective and less efficient dialogues.

The aim of the research described in this paper is to assess the extent to which multimodal in-put/output can help to improve effectiveness, ef-ficiency and user satisfaction of information systems in comparison with unimodal systems. This paper describes how, within the framework of the M ATIS1 (Multimodal Access to Transac-tion and Information Services) project we devel-oped a prototype of a multimodal railway infor-mation system by extending a speech-only ver-sion in such a way that it supports screen output and point-and-click actions of the user as input. This system is a typical example of a simple ap-plication that can be implemented using a slot-filling paradigm and may stand model for vari-ous other form filling applications.

First, a number of problems are described that arise in speech-only interfaces. Then we briefly describe the architecture of the speech-only 1 http://www.ipo.tue.nl/projects/matis/railway information system. Next, we describe in more detail how we added multimodality to this version of the system and explain why we think this may help to solve the shortcomings of speech-only systems. We conclude this paper by discussing several open issues that we intend to solve by means of user tests with the multimodal system.

2Shortcomings of speech-only interfaces One of the issues that all dialogue systems with spoken input have to cope with is the imperfec-tion of the speech recogniser. Even in very lim-ited domains and with a small vocabulary speech recognition is never 100% accurate, if only be-cause people may use OoD (Out of Domain) or OoV (Out of Vocabulary) words. To ensure that the user does not end up with wrong informa-tion, all slot values entered by the user must be confirmed. This can be done either explicitly in a separate question or implicitly, i.e. incorpo-rated in the next question. Explicit confirmation results in a lot of extra turns, which means that the dialogue becomes less efficient and is often perceived as tedious, especially if all user utter-ances are understood correctly. Implicit confir-mation, by contrast, does not necessarily in-crease the number of turns. However, it appears that users have difficulty in grasping the concept of implicit confirmation [Sturm, 1999]. Things run smoothly as long as the information to be confirmed is correct. If the speech recognition result is incorrect and wrong input expressions are confirmed implicitly, users tend to get con-fused and fail to repair the mistake that was made by the speech recogniser.

In order to reduce the need for confirmation, confidence measures may be used. A confidence score is an estimate of how certain one can be that the recognition result is indeed correct. Us-ing confidence scores in combination with one or more thresholds, would for instance allow to decide upon 1) ignoring the recognition result (if the confidence is minimal), 2) confirming the

recognition result or 3) accepting the recognition result without confirmation (if the confidence is maximal). Unfortunately, it is virtually impossi-ble to define thresholds in such a way that no false accepts (a user utterance is actually mis-recognised but has a confidence score that ex-ceeds the threshold) and no false rejects (user input was recognised correctly but has a confi-dence score that falls below the threshold) are caused. False rejects are not very harmful, al-though they do cause superfluous confirmation questions, and thus reduce the efficiency of the dialogue. False accepts, however, may become disastrous for the dialogue, since they cause in-correct values to be accepted without any con-firmation. As a consequence, this strategy does not seem very attractive for speech-only sys-tems.

Another problem with speech-only information systems is the way in which the eventual infor-mation is presented to the user. Shadowing ex-periments with different railway information systems indicate that users have difficulties un-derstanding and writing down a travel advice presented in spoken form, especially if one or more transfers are involved [Claassen, 2000]. Last, and perhaps foremost, it appears that users have difficulty in building a correct mental model of the functionality and the status of a speech-only system. This lack of understanding explains problems with exceptions handling, and the user’s uncertainty as to what one can (or perhaps must) say at any given moment.

3Multimodality in M ATIS

The first goal of the MATIS project is to inves-tigate to what extent graphical output along with speech prompts can solve the problems that are due to the lack of a consistent mental model. If, for example, recognition results are not only confirmed (implicitly) in speech prompts for ad-ditional input, but also displayed in the corre-sponding field on the screen, detecting recogni-tion errors may become easier. The same should hold for navigation through the list of possible connections that is returned after the input is complete and a database query can be per-formed.

If no keyboard is available speech is ideal for making selections from long implicit lists, such as the departure city. However, other fields in a form may offer only a small number of options, which can easily be displayed on a screen. In the railway information system this holds for the switch that identifies the time as departure or ar-rival time (and to a large extent also for entering the date, which usually is today or tomorrow). Selections from short lists are most easily made by means of point-and-click operations. There-fore, we decided to add this input mode to speech input.

3.1 System Overview

Our multimodal railway information system is an extended version of the mixed-initiative speech-only railway information system (OVIS) developed in the NWO-TST programme2. This is a very different starting point from most other projects in multimodal human-machine interac-tion, that seem to add speech to what is basically a user-driven desktop application. The user in-terface consists of a telephone handset in combi-nation with a screen and a mouse. The MATIS system inherited an architecture in which mod-ules communicate with each other using TCP socket connections under the control of a central module (Phrisco) (cf. Figure 1). The grey shaded modules have been added or extended for M ATIS.

Point & click input

Figure 1 Overview of the M ATIS system

In the next sections we will focus on the mod-ules that have been added or changed and how these modules help to solve some of the prob-lems described in Section 2.

2 http://odur.let.rug.nl:4321/

3.2 Screen output

At the start of a dialogue an empty form is shown on the screen. In the course of the dia-logue the fields are filled with the values pro-vided by the user, who can use speech to fill all five slots in the form in a mixed-initiative dia-logue, or use the mouse to select text fields and to make list selections. Once all slots have been filled, a travel advice is retrieved from the data-base and presented to the user in spoken and in textual form.

3.3 Mouse input

Experiments have been conducted using a Wiz-ard of Oz simulation of the M ATIS system, to establish to what extent subjects use the mouse in addition to speech and in what way mouse in-put is used in an interaction that is essentially the original mixed-initiative spoken dialogue [Terken, 2001]. It appeared that half of the sub-jects used mouse input as well as speech input and that mouse input was primarily used to make selections from short lists, and much less to select editable text fields. The latter was done mostly in the context of error correction.

3.4 Confidence calculation

Confidence measures (CM) for spoken input can be calculated in different ways. In the M ATIS system the CM is based on an N-best list of sentence hypotheses that is generated by the speech recogniser [Rüber, 1997]. This N-best confidence score rests on the assumption that words that occur in more entries in the N-best list are more likely to be correct:

where P(h i ) is the likelihood score of sentence hypothesis i in the N-best list. In this manner a CM is calculated for each word in the utterance.The N-best CM may give rise to a specific problem: if the N-best list contains only one en-try, (1) automatically yields a maximum confi-dence score for each word in the utterance. Off-line experiments have shown that 3% of all N-best lists consisting of only one sentence actu-ally contained recognition errors. Consequently,even if we only trust words with a maximum CM score, the false accept rate will be at least 3%. Other off-line experiments have shown that some improvement may be expected from com-

bining the N-best CM with another CM that does not have this artefact.

When a user fills a specific slot in the form us-ing speech (s)he has to indicate which slot needs to be filled and provide a value for this slot. To obtain a CM for the slot value, the CMs of all words that were used to specify this value have to be combined. In the current implementation this was done by taking their mean.

3.5 Multimodal Input Event Handler

The information coming from the NLP module (in response to a spoken prompt) and from the mouse (that is active all the time) must be prop-erly combined. This task is taken care of by the multimodal input event handler. To combine the information streams correctly, a time stamp must be attached to the inputs, indicating the temporal interval in which the action took place. This time interval is needed to decide which events should be combined [Oviatt, 1997].

Furthermore, speech and mouse input may con-tain complementary, redundant or unrelated in-formation. Complementary information (e.g.clicking on the ‘destination’ field and saying ‘Rotterdam’) is unified before it is sent to the dialogue manager. Unrelated information (e.g.clicking to select departure time while saying one or more station names) is first merged and then sent to the dialogue manager. In the case of redundant information (e.g. clicking on ‘tomor-row’ while saying ‘tomorrow’), the information coming from the mouse is used to adapt the CM score attached to the speech input. Due to speech recognition errors, ‘redundant’ information may be conflicting (if the recogniser returns ‘tomor-row’ in the same time slot where ‘today’ is clicked). To solve this problem the information with the highest CM score will be trusted.

3.6 Dialogue management

The dialogue manager of the unimodal system was adapted in order to be able to use the CMs to decide on the confirmation strategy. In the present prototype we use only one threshold to decide upon the strategy. Values with a CM score below the threshold are shown on the screen and confirmed explicitly in the spoken dialogue. Values with a CM score exceeding the threshold are only shown on the screen. In case all or most values have a high CM score, this strategy speeds up the dialogue considerably.Preliminary experiments suggest that providing feedback visually as well as orally helps the user

∑∑=∈==

N i i

N

h W i i nbest h P h P CM i 1

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((1)

to develop an adequate model of the system. Also, since the user knows exactly what the in-formation status of the system is at each point in the dialogue, correcting errors should be easier, which in turn will result in more effective dia-logues. We are convinced that an increase in ef-fectiveness and efficiency can be achieved, es-pecially if the visual output is combined with auditory prompts that are more concise than in the speech-only system.

3.7Multimodal Output Event Handler In a multimodal system a decision has to be made as to whether the feedback to the user must be presented orally, visually, or in both ways. This is the task of the multimodal output event handler. For the time being we have de-cided to send all the output from the dialogue manager to the natural language generation module and the screen.

4Discussion and conclusions

In this paper we have described the architecture of a multimodal train timetable information system that was built by extending a speech-only version. Most of the desired functionality of the modules that we added or changed was specified on the basis of off-line experiments and findings in the literature. The system is now ready to be tested by real users.

Adding visual feedback has been shown to help in several respects. In Terken (2001) it was shown that the visual feedback helps the user to build a mental model of the task at hand. Fur-thermore, we argued that visual feedback may be interpreted as a form of implicit verification, which helps the user to detect recognition errors. This allows to apply confidence thresholds to avoid confirmation turns, even if a number of false accepts occur. This is in contrast with speech-only systems, where false accepts will remain unnoticed.

User tests with our present prototype are needed to verify whether the additional modalities do indeed help to increase efficiency, effectiveness and user satisfaction. These tests will be con-ducted in the near future. In the current proto-type a number of ad hoc choices were made. We expect that several of these choices will have to be revised based on the outcomes of the tests. CM scores that are calculated for individual words must be transformed into scores for slot/value pairs. This can be done in several ways: by taking the mean score, the maximum score, weighting the scores for values and slots, etc. In the current prototype we take the mean of the scores of the words that yielded a certain slot/value pair, but more sophisticated methods may be needed.

In principle it is possible to go beyond the cur-rent design and give feedback on the status of the slots (confirmed or not, changeable or not) in addition to showing their values. This might prevent the user from getting lost in the dia-logue. However, it is not yet clear whether addi-tional visual attributes can be designed that are self-explanatory and will not confuse the user. It might be useful to enable the user to correct in-formation by clicking the field that contains in-correct information and saying the correct in-formation. Also, showing a list of alternative recognition hypotheses from which the user can select the correct one, might help. In the current system we have not implemented this option. Currently, the complete output of the dialogue manager is sent both to the speech output mod-ule and the screen. Informal tests have shown that the speech output designed for a speech-only system is much too verbose. Especially the oral presentation of the travel advice can be a short summary, e.g. consisting of only the de-parture and arrival times, when the complete ad-vice is also presented on the screen.

5Acknowledgement

This work was supported by a grant from Sen-ter/EZ in the framework of IOP-MMI.

6References

B. Rüber (1997), Obtaining confidence measures from sentence probabilities,Proceedings Euro-speech’97, pp. 739-742.

W. Claassen (2000), Using recall measurements and subjective ratings to assess the usability of railroad travel plans presented by telephone, Technical Re-port #123, NWO Priority Programme on Language and Speech Technology.

S. Oviatt, A. DeAngeli, and K. Kuhn (1997), Inte-gration and synchronization of input modes during multimodal human-computer interaction, in Pro-ceedings of CHI '97, pp. 415-422.

J. Sturm, E. den Os and L. Boves (1999), Issues in spoken dialogue systems: Experiences with the Dutch ARISE system,Proceedings ESCA Work-shop on Interactive Dialogue in Multimodal Sys-tems, pp. 1-4.

J. Terken and S. te Riele (2001), Supporting the con-struction of a user model in speech-only interfaces by adding multimodality,Submitted to Eurospeech 2001.

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bring的详细用法

1. Bring 带来;拿来;领来?Did you bring an umb rella? 你带伞了吗? bring sb/sth to sb/sth ?Is it OK if I bring some friends to the party? 我带几个朋友来参加聚会行吗? bring sb/sth with you ?For some reason, Jesse had brought a tape recorder with him. 不知为什么,杰西带了一台盒式录音机来。 bring sb sth ?Can you bring me another beer? 你再给我拿一杯啤酒好吗? bring sb/sth to sb/sth ?He expects me to bring everything to him. 他指望我什么东西都给他带去。 2.引起〔某种情况或情感〕,造成,导致?efforts to bring peace to the region 给这个地区带来和平的种种努力?The strikes are expected to bring chaos. 预计罢工会造成混乱。 使处于某种状况?It was the war that first brought him to power (= make him have power over a country ) . 是战争首次将他推上权力宝座。 ?Bring the sauce to the boil (= heat it until it boils ) . 把调味汁煮沸。 bring sth to an end/a close/a halt/a conclusion 使某事结束?The trial was swiftly brought to an end. 庭审匆匆就结束了。 3.使朝某个方向移动bring sth up/down/round etc ?Bring your arm up slowly until it’s level with your shoulder. 慢慢举起手臂到齐肩的高度。?The storm brought the old oak tree crashing down. 暴风雨把这棵老橡树刮倒了。 4.促使某人去…what brings you here? (=used to ask why someone is in a particular place)什么风把你给吹来了? 5.带来〔可供人们使用、拥有或享受的东西〕;使得到;创造 ?The expansion of state education brought new and wider opportunities for working class children. 公立教育的普及为工人阶层出身的儿童带来了更多新的机会。 bring sth to sb/sth?The government is launching a new initiative to bring jobs to deprived areas. 政府正在出台一个新的方案,为贫困地区创造就业机会。 bring sb sth?It’s a good sign –let’s hope it will bring us some luck. 这是一个好征兆——但愿会给我们带来好运。 6.〔某段时间〕带来;使发生 ?Who knows what the future will bring? 谁知道未来会发生什么?

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Passage 8: One cognitive theory suggests that aggravating and painful events trigger unpleasant feelings. These feelings in turn,can lead to aggressive action,but not automatically. Cognitive factors intervene. People decide whether they will act aggressively or not on other people’s motives. Supporting evidence comes from research showing that aggressive people often distort other people’s motives. For example, they assume that other people mean them harm when they do not. The word distort in the passage is closest in meaning to ○ mistrust ○ misinterpret ○ criticize ○ resent 解析:distort所在的文章句子后出现“ for example”,根据for example 中的内容,我们可以得出distort在此句中的意思为misinterpret。 3. 并列信息 Example: OG Practice Set 5,question 3 Passage 3: …Absenteeism and lateness hurt productivity and since work was specialized,disrupted the regular factory routine. Industrialization not only produced a fundamental change in the way work was organized; it transformed the very nature of work. The word disrupted in the passage is closest in meaning to ○ prolonged 托福阅读词汇分类技巧(一) https://www.360docs.net/doc/8f9336022.html,/tuofuyuedu/20141219/329225.html?seo=wenku

For-example与such-as的用法及区别

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科技教育活动方案培训讲学

科技教育活动方案

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同的需求,树立材料意识,同时可以使学生具有准确的辨识能力、分析能力和敏感的科学触觉。 ⑵在自制玩具的过程中,训练动手技能,培养学生的动手能力和独立思考的能力,发展个性,养成良好的科学探索习惯。 ⑶通过采访、讨论、交流,培养学生的口语表达能力和人际交往能力。 2.情感态度和价值观 ⑴获得亲自参加活动的积极体验和丰富经验,塑造完美人格。 ⑵掌握一种科学的思维方式和独特、科学的实践方法,善于从身边进行科学实践。 ⑶鼓励学生积极参与制作,引导学生综合运用知识,培养学生克服困难的勇气和意志力,促进合作精神。 ⑷体验科学技术在生活中的作用,激发学生自制玩具的兴趣,不断进行尝试和创新,尊重自己和他人的制作成果。 (三)活动重、难点和创新点 重点:做个生活的有心人,把废旧物品再利用,重新整合设计,变成点缀生活的有趣小玩意。 难点:学生手脑并用,亲自经历制作过程。 创新点: 1.学生有浓厚的兴趣,容易调动学生的积极性。 2.适用范围广(小学生、中学生都可参加),成本低,普及性强,可组织多人参加活动。 3.参加活动学生的自主创新意识得以充分发挥。 4.在普及的基础上,每年可以组织全校学生参加创意大赛,将会涌现出许多小发明创造。 5.增强学生的环保意识。 (四)活动原则 1.实践性。学生把理论知识转化为实践经验的过程,是一种学生自己动手制作亲自经历的活动,是科技教育的灵魂。在活动中,重在学生参与,发挥他们的主体作用。让学生亲自选材、亲自设想设计、亲自制作、亲自介绍、亲自评价。 2.激励性。在整个科技教育过程中注重发挥激励功能,这里没有失败,只有不断的探究。每个学生在大家的热切期待中体验了制作的全过程。

北京芸学教育科技有限公司

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