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Spoken Dialogue Technology Achievements and Challenges

Spoken Dialogue Technology Achievements and Challenges. Michael McTear University of Ulster. Overview. Introduction - What is a spoken dialogue system? Examples of spoken dialogue systems Technical issues and challenges Future Prospects. What is a spoken dialogue system?.

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Spoken Dialogue Technology Achievements and Challenges

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  1. Spoken Dialogue TechnologyAchievements 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. Problem-solving – to support the user in solving a problem e.g. to troubleshoot a PC that is not working 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

  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 … http://www.speechstorm.com/

  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 http://groups.csail.mit.edu/sls/research/mercury.shtml

  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 1-800-GOOG-411 from any phone, anywhere, at anytime. http://www.google.com/goog411/

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

  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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