Improved call completion with Natural Language Processing Peter Trompetter

2. “Just simply say it” Improved call completion with Natural Language Processing Peter Trompetter Vice President Global Development contact@GyrusLogic.com www.GyrusLogic.com (+1) 602 - 432 1995

3. DTMF / IVR WWW Speech IVR Speech NLU TUI / Spoken Data Out GUI / Graphical Data Out VUI / Spoken Data VUI / Natural Language Late 1970’s Early 1990’s Late 1990’s Early 2000’s Evolution of Self-Service Solutions

4. The Economics of Service Levels • On average, every 1 percent increase in first contact resolution results in a 0.64 % increase in customer satisfaction. • On average, with every 1 second decrease in the average speed of answer, customer satisfaction improves only 0.03 % • Focusing on things that drive first contact resolution generally creates greater customer satisfaction and is often less costly than focusing on things that improve the average speed of answers

5. Typical Natural Language Dialog System: How may I help you? User: I would like to make a reservation for a flight to Chicago on July 17th System: At what time and from what city do you want to travel? User: In the morning from Phoenix, Arizona System: OK, you could travel at 10 am. On Wednesday July 17th from Phoenix to Chicago. Do you want to make this reservation? User: What are my options? System: On July 17th you could travel at 10am., noon and 2pm. Do you want to make the reservation for the 17th at 10am? User: No, I would like to go on the 7th. In the afternoon. System: OK, you like to travel at 2pm on Sunday July 7th from Phoenix to Chicago. Do you want to make this reservation? User: Yes, can I make a seat selection? System: Based on your customer profile we assigned a window seat 9A. Would that work for you? User: Yes, thank you. System: Let’s confirm your reservation, you are traveling on Sunday July 7th. at 2pm from Phoenix to Chicago and we assigned you seat 9A. Do you want to purchase this ticket and confirm the reservation? User: Yes, perfect! System: OK, reservation completed. How else may I help you? Note how the user can be spontaneous and say as much as he wants Interruption of dialog with any question, even if it was unrelated The system resumes the previous dialog and requests the missing information The system still handles the question effectively without coding of additional rules User can make a correction on the fly at any point in time

6. voice self service Voice Self Service Savings Opportunity

7. Typical Call Center Voice Metrics • Speech recognition application • Overall automation rate • Speech play rate / don’t play rate • Zero-out and call abandon rate • Transaction / query completion rate • Prompt / conversational usability rate • Call duration • Call completion rate • Customer satisfaction metrics

8. Speech Technology IBM, Microsoft, Nuance, Scansoft, Telisma Text to Speech Several suppliers Platform providers Industry standards Hardware Languages, tools VoiceXML / SALT IVR / CTI functions Hosting vs. on premise Application development Industry standards languages, grammars, tools Existing available skills Development environment Development standards Development time Development budget Maintainability In house vs. outsourcing Packaged applications Business and Customer benefits Selecting a Speech Solution

9. Speech Deployment Metrics Professional Services > 60%

10. DTMF Dual Tone Multi-Frequency Speech enabled IVR “Press or say one” Directed dialog Voice prompted menu Open dialog “How can I help you?” Significant limitations The menu challenge Not really an enhancement Typical start with speech still the menu, correction and confirmation frustration Natural language an answer at first contact Selecting your “Voice” Application

11. Natural Language Understanding • Typical ASR approaches for Natural Language Understanding (NLU) • Statistical Language Modeling (SLM) • Statistical Semantic Modeling (SSM) • “Say Anything” - Nuance • “Speak Freely” - ScanSoft • Transcription of 20,000 - 30,000+ utterances • Complex long scripting procedures • Keyword or Word spotting, interpretation difficulties of output phrases • Procedural developments

12. Another NLU Approach • Artificial Intelligence technology build with computational linguistic models for a fully automated conversational dialog. • No dialog design is necessary, since the system knows how to adapt dynamically to the requirements of the natural conversation. • Declarative development process. • Selectable automated text and / or audio responses. • At any time requests can be spontaneous, no static menus. • User requests can be specific or vague, the system will answer the question any way. • Automatic explicit orimplicit corrections. • Rating for "n-best" ASR results based upon meaning and context.

13. Another NLU Approach - Tools • Easy to use Java API • Standard integration templates for a quick interface to an IVR or VoiceXML browser. • Language development tools and templates for adding new languages or unique words to existing language dictionaries. • XML interface for building a quick interactive application knowledge base. • Standard universal English grammar. • Standard templates for easy interaction with enterprise databases. • Automatic static and dynamic speech grammar generation. • Batch test tool for quick dialog testing.

14. Typical Two Types of NLU Requests • Fuzzy (informational) • They can be spontaneous, arbitrary, ad-hoc, and/or vague • The majority of user queries are fuzzy questions • If not all the information is available, users prefer some information rather than no information • Exact (transactional) • Specific transactions don’t allow for fuzzy approach, but they can still be spontaneous • Transfer 100 bucks from checking to savings • Travel at 3this afternoon from Phoenix to Burbank • Did check number 123 clear on July 1st.?

15. Application Implementation • Defining the application, Natural Language Understanding or Directed Dialog or any Combination of both. • Initial functional application requirements • Document possible caller requests / answers • Separate transactional requests • Generate grammar for transactional requests (BNF) • Develop a XML based state machine for transaction requests • Universal Grammar for informational requests provided • Use template answers for informational “fuzzy” requests • Document sample answers • Parse corpus of questions • Identify the Enterprise backend dB interfaces (XML)

16. GyrusLogic Language Support • Today, users can build any grammar for their specific application in any language in a matter of hours. • With GyrusLogic, languages are supported by composition of dictionaries and grammars. • Language specific dictionaries and grammars are kept outside the GyrusLogic engine and are standard text files, allowing users to easily provide a new or updated content to a language. • For Fuzzy requests we do provide a universal grammar of English, a user doesn't have to compose anything. • New language Universal Grammar development can be completed in several days, utilizing specific language experts / natives. • GyrusLogic language limitations are based upon the languages supported by the ASR used.

17. Corpus for Fuzzy queries static grammar & dictionaries Speech Grammar Generator (static grammars) User’s Gyrus ABNF grammar User XML with embedded grammars ASR dynamic grammar GyrusLogic Server GyrusLogic Client/API Speech Grammar Generation Process

18. Typical Natural Language Dialog Note how the user can be spontaneous and say as much as he wants System: How can we help you? User: I would like to transfer funds from my checking to my savings. System: How much money do you want to transfer? User: How much money do I have in my savings account? System: The balance in your savings account is 4000 dollars. I apologize for asking again, how much did you want to transfer? User: Five hundred. System: Ok, let's review this transaction, you want to transfer 500 dollars from your checking to your savings, is this correct? User: No, actually transfer a thousand bucks from savings! System: Ok, let's review this transaction, you want to transfer 1000 dollars from your savings to your checking, is this correct? User: Yes System: How else can we help you? User: What are the last five transactions in my checking? System: The last three transactions in your checking account are…. Interruption of dialog with any question, even if it was unrelated The system resumes the previous dialog and requests the missing information User can make a correction on the fly at any point in time The system still handles the question effectively without coding of business rules

19. + 10 times less effort VoiceXML Mixed Initiative Example • A Natural Language solution is more spontaneous! • Exponential savings for more complex applications A benchmark with a web published VoiceXML example: Agent: Thanks for calling Acme Travel Company. How can I help you today? Caller: I'd like to book a flight. Agent: Okay. What is your point of origin, and where are you going? Caller: I wanna fly to Boston, Massachusetts. Agent: You want to fly to Boston, Massachusetts. Where are you flying from? Caller: From San Francisco, California. Agent: Okay, you'll be traveling from San Francisco, California to Boston, Massachusetts. Is that correct? Caller: Yes.

20. How does a GyrusLogic NLU solution help? • Declarative vs. Procedural or Icon based developments. • Open industry standards system and development environment. • Implicit and Explicit corrections without additional coding. • Spontaneous user interruptions in any call flow without additional development effort. • Context and semantics recognition at any point in the dialog. • Significant savings in time and money with the deployment and maintenance of GyrusLogic based NLU applications. • The same application can be used for Voice, chat, web and SMS. (text messages)

21. Add the Advantages of NLU • Give the right answer at the first request! • No dialog design, flat “menu” with “How can I help you”, human like full conversational. • Managing distinctions between fuzzy informational queries and exact transactional queries. • Implicit and explicit transaction correction functionality. • With a declarative development paradigm, developments will be significantly less error prone and less timeconsuming than with other procedural developments. • Virtually no language dependency. • ASR and TTS independence, interfaces with VoiceXML or your existing IVR.

22. Improved Call Completion with Natural Language Processing • First contact customer resolution achieved • Increase in customer satisfaction accomplished • Reduced relative call time accounted for • More transactions / requests completed automatically • Combine Directed Dialog with NLU and create additional application opportunities • NLU has transitioned from “emerging” to “applied” solution • Improved call completion with a full conversational natural language processing approach will result in significant cost reduction.

23. Average Speech Deployment Costs A minimum of 27% project costs savings Source: Voice Information Associates, ASR in Telephony Applications, the World Market

24. Thank You! “Just Simply Say It” Questions or you want to know more about our Natural Language Understanding solutions? please contact us at: http://GyrusLogic.com- (+1) 602 - 432 1995 -contact@GyrusLogic.com JustSimplySayIt.com