1. Inference Communications Grammatical Inference real world implementations..a new approach in practice Callan Schebella VP Business Development Inference Communications

2. What is Grammatical Inference? Grammatical Inference is both: –a technology –a development methodology ← Grammatical Inference is the process of using machine learning techniques to automate the development of spoken dialog systems. –any kind of speaker-independent system where grammar is of key importance –In particular building speech recognition systems for call center environments ←

3. Classic Development Methodology Speech recognition engagements typically follow the following pattern: 1.Discovery (Requirements Analysis) 2.Simulation (Wizard of Oz) 3.Prototype 4.Pilot (limited functionality) 5.Deployment 6.Post Deployment

4. Speech recognition engagements typically follow the following pattern: 1.Discovery (Requirements Analysis) 2.Simulation (Wizard of Oz) 3.Prototype 4.Pilot (limited functionality) 5.Deployment 6.Post Deployment Grammatical Inference “Proof of Concept” 1–3 Days Classic Development Methodology

5. Grammatical Inference - the methodology Grammars and call flow are developed right from the start and are developed concurrently. –Sketch the call flow (usually with the customer) and then add the detail incrementally –The sketch defines the underlying grammars the ‘slots’ to be filled & the ‘types’ that will fill them Typically 1 – 2 hours –Example phrases are then provided to train and build the grammar automatically. “Grammar centric” Vs. “Call Flow centric”. –The aim is to get something you can talk to as quickly as possible.

6. Grammatical Inference cont.

7. Define overall call flow

8. Grammatical Inference cont. Define grammars in terms of slots

9. Grammatical Inference – in practice Where is it used? –Potentially, at every stage of the SDLC Requirements analysis –Collect customer requirements on the spot. Prototype development –Getting something to talk to Full application development –Traditional development processes Maintenance –Post deployment tuning

10. Continuous Speech Improvement

11. Still early days Focus to date has been on prototyping. –Many customers no longer satisfied with a prepackaged application or audio file. A prototype: 1.Makes speech tangible –Nothing changes perception like an actual telephone number. 2.Develops buy in from the stakeholder groups –They can interact with a prototype in their own time. 3.Highly effective at overcoming the key challenges in selling speech…

12. Grammatical Inference & Prototyping Common challenges: –Possibility: Does speech even work? “Company XYZ used speech recognition and they had problems.” Natural language – “They won’t believe it until they hear it!” –Suitability: But my company is different. “My customers don’t talk like that.” “I need to talk to it”. “I want some people to try it first” – Internal Selling –Viability: Ok it works – but how much did that cost? “What about the hidden costs?” “I want to measure the performance”.

13. Different stages = different prototypes Recognize that different customers are at various stages of the process: –Building prototypes for different purposes. –Tailoring each prototype to achieve the outcome required. Proving the Concept Assessing the Suitability Proving the Viability –Grammatical Inference is the ideal development methodology for getting answers to these questions with the minimum amount of cost and the minimum amount of time.

14. Case study #1 - Health Insurance New to speech Required natural language Had specific enquiries that were not common to many industries

15. Case study #2 – Public Transport Had experience with speech, wary of promises Huge number of diverse stakeholders Customer charter – significant accessibility requirements

16. Case study #3 - Australia Post Massive organisation Speech used in some areas – but not in others ROI driven on a case-by-case basis (internal selling)

17. Conclusion Each customer was at a different point in the process. …by illustrating the required functionality the customer was able to progress to the next stage. Very Cost Effective: –The most intensive demonstration only took 3 days from start to finish. –The prototypes became the starting point for the real system – evolutionary prototyping model. –The challenge is now to move from prototyping to full application development.

18. Inference Communications