White Paper T A L K T O Y O U R W A R E H O U S E : S P E E C H R E C O G N I T I O N C O M E S O F A G E

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1 White Paper T A L K T O Y O U R W A R E H O U S E : S P E E C H R E C O G N I T I O N C O M E S O F A G E

2 Introduction Spoken input for warehouse and other industrial operations has traditionally been easy for workers to use, tougher for IT staff to integrate and support, and harder still for business and finance managers to justify. Users love the flexibility of having their hands and eyes free from working mobile computers and the convenience of talking to record activity. IT staff enjoyed no such flexibility at the back end of the system, where traditional voice recognition technologies require significant integration and customization to work with existing warehouse management systems (WMS) and other enterprise applications. Operational needs for continuous productivity improvement of warehouse and manufacturing operations continue to increase with changing order profiles, increasing customer demands for new services and less restrictive ordering policies. Voice has demonstrated a positive impact on productivity and safety by keeping users focused on the task at hand in a hands- and eyes-free environment, and could offer great benefits to many operations. But the high cost and risk associated with integrating traditional voice recognition systems has limited adoption to a small percentage of operations. A new method of implementing speech input removes many of the costs, implementation risks and application limitations. By using terminal emulation (TE) with support for IBM 3270, IBM 5250, VT220 and ANSII to format and process speech input/output, data flows into existing software applications as if it had been entered by bar code scanning, key entry, or whatever method was previously used. No additional, proprietary interface between the speech system and application software is needed. Terminal emulation is already widely used as the interface between rugged mobile computers and enterprise applications to control inventory, warehousing, delivery inspection, retail store and other operations. Now TE users can easily supplement their operations with efficient speech input and commands, without costly software redevelopment or adding a separate voice application and server layer to their systems. Many operations can now take advantage of the flexibility and productivity improvement that speech provides without replacing existing enterprise applications. This white paper will briefly review traditional voice recognition systems, compare the performance of various data collection technologies, highlight the advantages of speech integrated with terminal emulation, and provide an overview of Intermec s TE2000/Speech solution. Traditional Voice Recognition Systems Traditional voice recognition systems are used primarily for item picking activities in a warehouse environment, with limited deployments in inspection, cycle counting and other industrial applications. The primary benefit is the increased productivity that comes from keeping the user s hands and eyes free. Users can pick many more pieces per hour when they don t have to interrupt their workflow to look at a computer screen to receive their next task. Various case studies and research reports have shown that productivity gains of 10 to 30 percent are common. Traditional voice recognition systems typically cost between $9,000 and $12,000 per user to implement (including server and integration costs). The technology has been proven to positively impact operational efficiencies but is not without its drawbacks. Cost, administrative tasks required to maintain system performance, integration challenges and loss of real-time interaction with the WMS have limited adoption of the technology. Traditional voice recognition systems work by recognizing the sound of a user s voice (vs. the actual words that are spoken), and require each user to train the system to recognize his/her unique voice and create a unique voice template. The voice template for each user is stored on a server dedicated to pushing the user s unique template to a specific mobile device when the user logs into the system. The effort required to train the system and create the template is relatively minor. However, when voice quality changes for some reason, such as a hoarse 1

3 voice or even nervousness during the training process, the voice template must be updated to maintain system performance. Administrative time is also required to manage the voice server. In warehouses with high employee turn-over, the process of maintaining templates can become cumbersome and expensive. Voice recognition systems are mostly used to provide input to warehouse management systems, so WMS applications and processes will serve as the example for how voice recognition systems operate. The warehouse management system downloads the tasks that will be managed through voice recognition input to the voice server. The server then handles interaction with the various users by issuing commands and instructions wirelessly to the mobile terminals, which direct workers using computer-generated audible commands through the headset. The voice server periodically updates the WMS application as transactions are completed, and receives new tasks to assign. The exchange between the WMS and the voice server requires complicated integration efforts for development and support. Because tasks managed through existing voice solutions must be communicated in batches, WMS systems don t operate in real time when interfaced with voice recognition systems. The lack of real-time inventory updates and transaction status information can cause problems in high-volume operations and when real-time visibility is needed for customer service or other business users. When working in batch mode, WMS systems also lose their ability to interleave tasks and provide real-time exception management and error correcting. Until recently, most voice recognition systems relied on their own purpose-built mobile terminals that didn t have ports or displays to support bar code scanning, RFID and other forms of automated data entry, leaving voice recognition as the only input option. This restricts the ability to add voice to supplement legacy applications and impacts the accuracy and efficiency of operations. For example, a voice-only system cannot make use of a 12-digit location code to verify location since the user cannot be expected to recite such a long number. To compensate for this, voice systems often employ a concept known as check digits. A check digit is a two- or three-digit identifier used in lieu of the location number. Check digits are more readily memorized than longer location numbers which weakens their effectiveness for validating the location. Special logic is often required to translate the check-digit into a location number that the WMS can understand. In addition, a voice-only system makes it impractical to record lot, serial or license plate numbers, which provide more precision and accuracy for warehouse operations, squeezing out the last 2-4% of errors. TE-based Speech Recognition Terminal emulation-based speech recognition systems provide all the operational benefits of voice recognition without the risks and headaches associated with its use. This revolutionary approach uses terminal emulation as the interface between the speech system and application software, maximizing the existing infrastructure to provide enabling technology. Because this approach is speaker independent (similar to that used in automated call and auto navigation systems), it eliminates the need to train the system through recorded voice templates. The approach also reduces implementation, integration and support cost because it eliminates the need for a separate voice server and for single-purpose voice terminals. WMS and other applications can continue to run in real time when used with TE-based speech input. Because it is based on open standards and designed to run on devices already widely deployed throughout warehouse and manufacturing operations, TE-based speech recognition costs an estimated 70% less per user to implement. TE enables speech recognition to function as a true input technology, not a separate application that has to be managed and integrated. Figure 1 compares the architectures of traditional voice and TE-based speech recognition. 2

4 Figure 1: System Architectures for Traditional and TE-based Speech Recognition Traditional Voice Recognition TE-based Speech Recognition ERP/WMS/IM ERP/WMS/IM Voice Server Business / Task Logic Voice Templates Batch Transactions Custom Interface (AIDC) R R Multi-modal using native TE Scanning Imaging RFID Keyboard User Interface R With Scanning Legend: = High risk/cost = Medium risk/cost = Low risk/cost Contrasting Efficiency & Accuracy Picking is a common application that well illustrates the differences among traditional voice, TE-based speech and bar code data entry methods. Consider a distribution center that picks 1.6 million cases per month using leading methods for picking: a mobile computer with integrated bar code scanning (mobile bar code scanning), traditional voice recognition, and a mobile computer using both TE-based speech recognition and bar code scanning (TE-based multimodal data collection). Figure 2 shows the accuracy rate for each method (based on industry-standard figures) and the number of full-time equivalent workers (FTEs) needed to handle the monthly pick volume using each method. Figure 2: Accuracy and Efficiency Comparison for Picking Processes Data Entry Method FTE Efficiency Rank Accuracy Rate Accuracy Rank Mobile Bar code Scanning % 1 (tie) Traditional voice recognition % 3 TE-based Multi-Modal Data Collection (Speech & Scanning) % 1 (tie) Speech and voice recognition technologies are more efficient than scanning technology alone. Keeping the operator s eyes and hands free creates productivity advantages other methods can t match. An operator can perform two tasks at once he can simultaneously move product and collect the data required to confirm the product movement, thereby condensing the overall time required to complete both tasks. Mobile bar code scanning requires more labor 3

5 than either speech or voice recognition because of the time required to operate the bar code scanner and confirm the transaction before or after the product movement. Scanning is therefore the least productive option, requiring 77 workers. Traditional voice recognition is the most efficient of the three methods, requiring only 51 workers to handle the same pick volume. At 99 percent accuracy, bar code scanning is more accurate than traditional voice recognition and on par with TE-based multi-modal data entry. Bar code scanning also allows data capture that isn t practical by speech or voice, such as entering serial numbers, lot numbers or other large character strings. Traditional voice recognition and TE-based multi-modal data collection have different accuracy rates because a TE-based multi-modal method still incorporates bar code scanning and operates with the warehouse management system in real time whereas traditional voice systems do not. Workers using traditional voice recognition systems aren t alerted to picking errors in real time, so mis-picked items can make their way into orders, lowering the accuracy rate. Accuracy rates for traditional voice recognition can be improved by developing check digits and shortcuts for data entry. However, these steps require additional programming, and therefore add to implementation and support costs. The absence of automatic data capture, including bar code scanning, imaging and RFID also limits the accuracy rates of traditional voice recognition solutions. As shown above. TE-based speech recognition, combined with scanning, doesn t have the tradeoff between accuracy and productivity that other methods require. TE-based speech recognition retains the labor-saving benefits of traditional voice-directed picking systems while matching the exceptional accuracy of bar code scanning. Comparative Costs & Application Implications The financial benefit of needing fewer workers is clear to see and easy to measure. But there s more to the value equation than labor. Accuracy and the cost of errors need to be factored in as well. Picking errors require administrative and distribution center labor time to correct, and may also result in a direct cost through chargebacks or fines. Businesses have been willing to accept the lower accuracy rate of traditional voice recognition technology relative to mobile bar code scanning because of the increased productivity they gain. With TE-based speech recognition, accuracy doesn t have to be sacrificed for efficiency. Interfacing directly with the WMS or other host application in real time puts TE-based speech recognition on par with bar coding for data entry accuracy, without reducing the traditional productivity benefits that hands-free data entry provides. Aside from the differing costs of implementation, the difference in picking accuracy and productivity of traditional voice and TE-based speech systems results have a financial impact on operations. The following graphs highlight these financial impacts. 4

6 As we saw earlier, traditional voice recognition is an efficient method requiring the fewest number of workers to handle the pick volume. Other methods require additional workers, thereby resulting in additional labor costs. Figure 3a shows the additional costs incurred by mobile bar code scanning and TE-based multi-modal data collection. Figure 3a: Incremental Productivity Costs $1,400,000 $1,200,000 $1,000,000 Costs $ $800,000 $600,000 $400,000 $200,000 $0 Traditional Voice Mobile Bar Code Scanning Multi-Modal Mobile bar code scanning and multi-modal data collection have the highest rates of accuracy (99%). Traditional voice recognition produces more errors, thereby requiring additional cost to correct errors. Figure 3b shows the additional costs incurred by voice recognition. Figure 3b: Incremental Accuracy Costs $1,400,000 $1,200,000 $1,000,000 Costs $ $800,000 $600,000 $400,000 $200,000 $0 Traditional Voice Mobile Bar Code Scanning Multi-Modal 5

7 Combining the costs of additional labor and additional errors shows the operational impact to the bottom line of each data collection method. Figure 3c shows that TE-based multi-modal data collection with speech and scanning results in the lowest incremental cost to the organization. Figure 3c: Total Incremental Cost $1,400,000 $1,200,000 $1,000,000 Costs $ $800,000 $600,000 $400,000 $200,000 $0 Traditional Voice Mobile Bar Code Scanning Multi-Modal The graphs above document the strong financial and operational benefits TE-based speech recognition can provide for picking operations. Additional cost benefits of TE-based speech recognition result from its easy integration with many legacy mobile computers and software applications. Because speech recognition through terminal emulation works as an input technology, not as a separate application, it can be adapted and leveraged to enhance other applications throughout warehouse and manufacturing operations with speech input/output. Existing systems don t need to be replaced. Example: Two Approaches to Receiving For example, speech input/output can enhance and improve a typical bar code-based receiving application. In the legacy, bar code-based process, the worker would select Receiving from the menu options on his or her mobile computer. An on-screen prompt would then ask the operator to enter the purchase order number for the shipment. The worker would then look up from the screen to locate the PO on a shipping label or other paperwork associated with the incoming material. After locating the PO number, the worker would enter it by keypad or bar code scanning, then follow on-screen prompts and proceed to record the contents of the shipment, again by scanning or manual data entry. Here s how speech input can simplify the operation and reduce the amount of times the operator has to look back and forth between the computer and the shipment. To start the process, the worker speaks Receiving into the computer. The application replies by saying PO number please into the worker s headset. All the while, the worker can keep his or her eyes on the shipment, to locate the PO number more quickly. The number is then entered by voice command or bar code scanning, whichever is more convenient. Once the PO is recorded, the application will confirm receipt audibly and ask the worker to Please enter first case number. Again, no check of the computer screen is required. Speech enhancement may only save a few seconds per transaction, but the aggregate time savings gained over thousands of transactions will provide a measurable productivity improvement. 6

8 Terminal emulation gives enterprises the flexibility to supplement many existing business processes with speech input. The technology is particularly effective when used to support cycle counting, inventory counts and directed putaway, and in many situations where it is beneficial to keep the worker s eyes and hands free. Conclusion The following table summarizes the key differences between traditional and terminal emulation-based speech recognition. Figure 4: Key Differences Between Traditional Voice Recognition and TE-based Speech Recognition Technology Features TE 2000 / Speech Traditional Voice Recognition Architecture Server required for template management 2 tiered speech clients connect directly to application software using terminal emulation. Supports real-time execution Yes No No 3 tiered voice clients interface with voice server, which is integrated with host software application through a proprietary interface. Avg. cost per user $3,500 $9,000 to $12,000 Technology Speaker-independent speech technology Accuracy rate 99% 95% Works concurrently with other data entry technologies Integration with application software Yes Terminal emulation By using terminal emulation, organizations don t have to make the tradeoffs between productivity and accuracy, and real-time responsiveness and user convenience that traditional voice recognition technology requires. TE-based speech recognition also makes it practical to use an assortment of automated data collection technologies as conditions warrant, rather than speech as the sole input method. By using common, familiar terminal emulation, eliminating proprietary interfaces and the need for an additional server, TE-based speech recognition becomes as easy for IT administrators to integrate and support as speech input is for workers to use. It s well accepted that speech input improves worker productivity, but concerns about support and integration requirements have made many companies hesitant to implement speech systems. Input by bar code scanning or manual data entry, while less efficient, remains the norm. TE-based speech recognition overcomes the cost, support and flexibility barriers of traditional speech recognition systems while improving accuracy and providing all the traditional productivity benefits. Intermec TE 2000 / Speech Solution Intermec s TE/2000 Speech product provides terminal emulation-based speech recognition. It is built on Intermec s TE 2000, which provides emulation for 3270, 5250 and VT/ ANSII environments, supports up to four concurrent sessions and wireless connectivity, and is supported by all leading WMS and enterprise software applications. TE 2000 has more than 450,000 users. Legacy and new users can now speech-enable their applications without having to give up bar code scanning and other types of input and legacy processes, and without adding another layer to their application infrastructure. Yes Speaker-dependent voice technology No Custom interface 7

9 T A L K T O Y O U R W A R E H O U S E : S P E E C H R E C O G N I T I O N C O M E S O F A G E The TE 2000/Speech application resides on mobile computers that support wireless communication and multiple input methods, including display, bar code, radio frequency identification (RFID) and key entry. Speech input/output is converted right on the computer and forwarded to the application software just as any other form of data input, enabling the mix-and-match of appropriate data-capture technologies on one transaction screen. WMS and application software interacts with the mobile computers in real-time as normal, confirming transactions and sending storage, picking and other such instructions, and is unaware if the data it receives was entered by speech, bar code, RFID or other method. The legacy terminal emulation for mobile computer and application software manages communication, with no custom integration or voice servers required. The solution can be used by any application that utilizes terminal emulation or telnet protocols to interface with mobile computers in a wireless network, and operates on a variety of handheld and vehicle-mounted mobile computers. Thousands of companies around the world rely on Intermec mobile computers and automated data collection equipment for warehouse, manufacturing and other industrial operations. By layering TE 2000/Speech with other data capture technologies in a single mobile solution, the same device can be used throughout an operation. Now these and other organizations have a cost effective and reliable way to integrate speech recognition into their entire operations. Contact Intermec to learn more about speech recognition and other automation options. Intermec Inc. (NYSE:IN) develops, manufactures and integrates technologies that identify, track and manage supply chain assets. Core technologies include RFID, mobile computing and data collection systems, bar code printers and label media. The company s products and services are used by customers in many industries worldwide to improve the productivity, quality and responsiveness of business operations. For more information about Intermec, visit or call North America Corporate Headquarters th Avenue West Everett, Washington tel: fax: nd Street S.E. Cedar Rapids, Iowa tel: fax: Media Supplies 9290 Le Saint Drive Fairfield, Ohio tel: fax: Canada 7065 Tranmere Drive Mississauga, Ontario L5S 1M2 Canada tel: fax: Europe/ Middle East & Africa Headquarters Reading International Business Park Basingstoke Road Reading RG2 6DD United Kingdom tel: fax: Asia Asia Regional Office #05-02A/03 New Tech Park 151 Lorong Chuan Singapore tel: fax: Beijing Representative Office 29 FL, Unit A1, China Merchant Tower 118 Jian Guo Road Chaoyang District, Beijing Tel: Fax: Australia Level 4, 1-3 Atchison Street St. Leonards, NSW 2065 Australia tel: fax: South America & Mexico Intermec South America Ltda. Rua Samuel Morse andar Brooklin CEP São Paulo, SP Brazil tel: Intermec Technologies de Mexico Av Tamaulipas #141, Primer Piso Col. Hipodromo Condesa Mexico, DF, Mexico tel: fax: Internet Sales (toll free in N.A.) tel: OEM Sales tel: Customer Service and Support (toll free in N.A.) tel: Copyright 2006 Intermec Technologies Corporation. All rights reserved. Intermec is a registered trademark of Intermec Technologies Corporation. All other trademarks are the property of their respective owners. Printed in the U.S.A A 11/06 In a continuing effort to improve our products, Intermec Technologies Corporation reserves the right to change specifications and features without prior notice.