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Spoken Dialogue Technology Achievements and Challenges

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Presentation on theme: "Spoken Dialogue Technology Achievements and Challenges"— Presentation transcript:

1 Spoken Dialogue Technology Achievements and Challenges
Michael McTear University of Ulster

2 Overview Introduction - What is a spoken dialogue system?
Examples of spoken dialogue systems Technical issues and challenges Future Prospects

3 What is a spoken dialogue system?
A spoken dialogue system is an automated system that engages in a dialogue with a human user using spoken language as the medium of interaction.

4 Types of dialogue system
Two main types of spoken dialogue system Task-oriented: involves the use of dialogues to accomplish a task, e.g. making a hotel booking, or planning a family holiday Non-task-oriented: engaging in conversational interaction, but without necessarily being involved in a task that needs to be accomplished e.g conversational companion for the elderly

5 Application Domains for SDS
Telephone-based services and transactions Call-routing, Directory assistance, Travel enquiries, Bank balance, Bank transactions, Flight / hotel / car rental reservations In-car interactive and entertainment systems Automated trouble-shooting Smart homes applications Health-care systems e.g. patient monitoring Educational e,g. Intelligent Tutoring Systems, Foreign Language Learning Computer games

6 Three generations of task-oriented spoken dialogue system
Informational – to retrieve information e.g. flight times, football scores, … Transactional – to assist the user to perform a transaction e.g. book a flight, pay a bill Problem-solving – to support the user in solving a problem e.g. to troubleshoot a PC that is not working

7 Why is dialogue interesting?
Fundamental aspect of human behaviour Model human conversational competence Simulate human conversational behaviour Provide tool for interacting with data, services, resources on computers Research challenges Applications in assistive and educational environments Commercial opportunities

8 Commercial Systems Focus on
Business opportunities, return on investment (ROI) Benefits for end users Benefits for providers Human factors: performance, usability Tools and languages for design and maintainability Application areas: call centre, enquiries, transactions, healthcare, …

9 Academic Systems Focus on
Technologies: speech recognition, spoken language understanding, dialogue management AI inspired: planning, reasoning, machine learning Statistical v symbolic approaches Advanced dialogue control, error handling, adaptivity, context representation

10 Overview Introduction - What is a spoken dialogue system?
Examples of spoken dialogue systems Technical issues and challenges Future Prospects

11 Example 1: Voice Menu System: Hello and welcome ….
Main menu. For customer service, say ‘service’. To enquire about an existing order, say ‘order’ … User: Service System: Customer service. Would you like to report a fault or enquire about an extended warranty? User: Fault System: Do you have a PC or a laptop? User: Laptop System: And the name of the manufacturer? User: Sony System: Thank you. Please hold while I transfer you to the Sony …

12 Example 2: Research System (Mercury: MIT)
Open ended prompt How may I help you? Disfluencies in input August twenty-first no August twelfth I'd like to fly from Boston to Minneapolis on Tuesday no Wednesday November 21st Inexact response Prompt: Can you provide the approximate departure time or airline preference User: Yeah I'd like to fly United and I'd like to leave in the afternoon

13 Example 2: continued Response generation
There are more than 3 flights. The earliest departure leaves at 1.45 pm. Mixed initiative: user asks question Do you have something leaving around 4.45? Relative date reference I’d like to return the following Tuesday

14 Example 3: Voice Search GOOG411
GOOG-411 (or Google Voice Local Search) is Google's new 411 service. With GOOG-411, you can find local business information completely free, directly from your phone. You can access GOOG-411 from any phone, anywhere, at anytime.

15 GOOG411: Prompts What city and state? What business name or category?
(Lists services) Number one, ….. Connects to requested service

16 GOOG411: What can you say? At any point in the call:
To go back say "go back" To start over say "start over" or press *All phones When asked for a city and state:  Say the full names for example, "Palo Alto California“ To enter a zip code say it or enter with keypad When asked for business name or category:  Say the full names for example, "Joe's Pizzaria" or "Pizza“ When given results:  To navigate between results say or press the listing number To receive an SMS say "text message" To receive a map say "map it" To get more details say "details"

17 Overview Introduction - What is a spoken dialogue system?
Examples of spoken dialogue systems Technical issues and challenges Future Prospects

18 Architecture of a spoken dialogue system
Speech Recognition (ASR) Back end Response Generation Text to Speech Synthesis (TTS) a --> xu Spoken Language Understanding (SLU) yu, c ã, c Concepts Words Audio HMM Acoustic Model N-Gram Dialogue Manager (DM) Dialogue Control Context Model a user dialogue act (intended ) c confidence ã user dialogue act (interpreted) xu user acoustic signal yu speech recognition hypothesis (words)

19 Component Technologies
Automatic Speech Recognition (ASR) Spoken Language Understanding (SLU) Response Generation (RG) Text to speech synthesis (TTS) Dialogue Management (DM)

20 Issues in ASR for Dialogue
recognising spontaneous speech in noisy environments word accuracy does not have to be 100% use of confidence scores in combination with other information to determine DM actions use of additional information (ASR and parse probabilities, semantic and contextual features) to re-score recognition hypotheses

21 Issues in SLU for Dialogue
grammars and parsers for spontaneous speech (disfluencies, errors) robust understanding problems with hand-crafted approaches use of statistical/ data-driven methods combined approaches e.g TINA (MIT) hand-crafted rules with trained probabilities robust strategy – if full sentence cannot be parsed, parse and combine fragments, else use word spotting

22 Issues in Response Generation for Dialogue
Content selection Determining what to say, selecting and ranking options Discourse planning discourse relations e.g. comparison, contrast user-adapted information Presentation ordering Referring expression generation Aggregation – grouping propositions into clauses and sentences Use of discourse cues (e.g. firstly, finally, however, moreover, …)

23 Issues in Dialogue Management
Dialogue Control Scripts, frames, intelligent agents Representations Information State Theory Error handling Dialogue design Traditional approaches Statistical approaches Reinforcement learning Corpus / example based approaches

24 Overview Introduction - What is a spoken dialogue system?
Examples of spoken dialogue systems Technical issues and challenges Future Prospects

25 A vision for the future Develop systems that can interact intelligently and co-operatively across a range of environments using a range of appropriate modalities to support people in the activities of their daily lives.

26 Fundamental research topics
Modelling human conversational competence Dialogue-related issues for ASR, SLU, NLG, TTS Comparison of methods for dialogue management: rule-based v stochastic Representation and use of contextual information Integration and usage of modalities to complement and supplement speech Incremental processing in dialogue

27 Areas of application Voice search Dialogue in vehicles
Mobile speech applications Multimodal embodied and situated systems Troubleshooting applications Dialogue systems for ambient intelligence and as assistive technologies

28 Concluding remarks Spoken Dialogue Technology
embraces a range of speech and language technologies poses lots of theoretical as well as practical challenges is interesting for commercial developers as well as academic researchers has a wide range of potential applications

29 Recommended reading McTear, M. (2004) Spoken Dialogue Technology. Springer. Lopez Cozar, R. & Araki, M. (2005) Spoken, multilingual and multimodal dialogue systems. John Wiley & Sons. Aghajan, H., Augusto, J.C., Lopez Cozar, R. (2009) Human-Centric Interfaces for Ambient Intelligence. Elsevier. Jokinen, K. & McTear, M. (2010) Spoken Dialogue Systems. Morgan Claypool Publishers. Wilks, Y. (ed.) (2010) Close Engagements with Artificial Companions: Key social, psychological, ethical and design issues. John Benjamins Publishing Company.

30 Thank you Questions?

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