The Fully Networked Car Geneva, 4-5 March Innovative Strategies to Improve the Delivery of Telematics Voice Services Julien Masson Director French Operations Connexis LLC

The Fully Networked Car Geneva, 4-5 March Consumers expectations for ubiquitous LBS o Consumers are more & more exposed to Navigation systems: Boom of the PND market Imminent explosion of GPS phone segment Steady increase of OEM Navi systems o They expect now to benefit from rich, up-to-date, dynamic content ubiquitously with easy-to-use location based services

The Fully Networked Car Geneva, 4-5 March Many attempts from OEMs to provide easy-to- use audio and visual in-vehicle services… o Using Navigation enhancement services whilst driving require a convenient, easy-to- use, and safe HMI (Audio, Visual, Tactile) o The Auto Industry has investigated over years various paths to enable services: Embedded Voice Recognition Assistance through a live Operator More…

The Fully Networked Car Geneva, 4-5 March Remaining Cost and Quality Challenges of In-Vehicle Audio Services o Despite these attempts, a number of cost and quality challenges remain for the delivery of in-vehicle voice services: Embedded Voice Recognition  Remains expensive with demanding CPU and storage  Not yet mature to address Open Natural Language Assistance Through a Live Operator  High Call Center operating cost vs. limited customer value  No local knowledge from operators

The Fully Networked Car Geneva, 4-5 March 2009 Key Industry Issue: Expensive Call Centre costs 5 Today’s Call centre costs are expensive compared to customers’ perceived value People-Assisted Computer Systems™ (PACS™) reduce traditional call centre costs, and streamlines the customer experience Expensive Call-Centre costs Connexis innovation

The Fully Networked Car Geneva, 4-5 March PACS™ : Flexible Call Center workflow Speech Recognition Engine (SRE) Silent Agent (Level 1) Agent Conversation (Level 2) Request Process PACS™ Workflow GPS Position / VIN + Request in Natural Language PACS™ is an innovative workflow processing customer’s voice requests using a hybrid of server- based speech recognition and human agents in reserve to assist in interpreting unclear commands SRE reduces operational costs and improves service delivery time Silent agents backup SRE without engaging the dialog with drivers Customer satisfaction is never compromised due to availability of L2 agent

The Fully Networked Car Geneva, 4-5 March SRE Speech Shell (SS) Necessary data for SS performance PACS Speech Shell requires three types of database: -Pronunciation data for POIs (dictionary) -Acoustic speech data to create acoustic models -Language data to create language models and grammars Speech Shell Dictionary Acoustic model Language model

The Fully Networked Car Geneva, 4-5 March Nearly 1000 requests performed in French language - 60% of requests are handled by Level1 and SRE -SRE/L1 < 50 sec., compared to ~2 min. (industry std.) PACS™ : Return on Experience Calls handling distribution Calls duration (Sec.)

The Fully Networked Car Geneva, 4-5 March 2009 Key Industry Issue: No Local Knowledgeable agents 9 Today’s Call centre agents are not the local experts that drivers require Micro Call Centre model of small groups of agents distributed geographically around regions to enable the “most local” agent approach to service delivery No Local Knowledgeable Agents Connexis innovation

The Fully Networked Car Geneva, 4-5 March 2009 Distributed Service Delivery 10 Agents handle requests in native language with local knowledge of roads, names, and landmarks Local knowledge reduces call times and increases customer satisfaction High quality VoIP with EC/NR Sophisticated, high-speed, server-based call routing, eliminating PBXs and ACD’s Ability to transfer calls smoothly ~15% cost reduction vs. traditional call centre Network of agents located where customers drive to provide the most locally knowledgeable service experience

The Fully Networked Car Geneva, 4-5 March Applying PACS™ and Distributed Call Centres to Telematics By combining speech recognition with human agents, PACS™: o avoids the current dissatisfaction of man to machine complex dialogs o reduces considerably labor costs o Never compromises customer satisfaction Distributed call centers with work-at-home agents promise to: o lower facility costs o solve the problems of scheduling and turnover o improving service with local knowledge Reductions in operation costs associated with more efficient/accurate service delivery opens up new business models