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These data, as well as other task-specific corpora provide the vital means to measure performance and progress For example, the Wall Street Journal (WSJ) corpus is intended for testing and developing dictation applications, and the Air Travel Information System (ATIS) was intended to help create automated dialog systems for travel information and improve spontaneous speech recognition NIST remains the custodian of the TIMIT database, and also provides robust evaluation and benchmark tests to assist the community with measurement and advancement of speech technologies Lastly, NIST also organizes and conducts the yearly NIST Speaker Recognition Evaluation tests These important government tests were initiated in 1996 and are of interest to anyone researching or developing text-independent recognition systems There is an enormous series of seemingly related patents concerning one aspect or another of speaker recognition Searching the US.

o far in our journey, we have covered in detail session beans, entities using the Java Persistence API (JPA), message-driven beans (MDBs), publishing stateless session beans as web services, and integrating all these components. On top of this, we have covered specific details on transactions and performance. While we have so far been developing simple command-line Java programs as our client applications simply to illustrate how the components work, we haven t thoroughly discussed the different types of EJB 3 client applications and how to develop them. In this chapter, we will discuss different application architectures in which client applications can be involved, and focus on building the common ones.

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(Summary of steps refer to LRFD sections) Non-compact section compression ange buckling: 1. Strength limit states I and II. 2. Construction limit state and uncured slab. 3. Refer to Section 6.10.5.3.3c and LRFD Eq. 6.10.5.3.3c Non-composite non-compact section lateral torsional buckling: 1. Positive and negative exure. 2. Strength limit states I and II. 3. Construction limit state and uncured slab. 4. Refer to Sections 6.10.5.5 and 6.10.6.4. 5. Lb 1.76 r1 (E/Fyc)1/2

The Java EE platform provides flexibility on how components can be distributed across different tiers and architectures. You can choose the right architecture and programming model based on the application or configuration requirements. In this section, we will look at the different possible architectures and programming models that you can use. Figure 12-1 shows the architectural layout for web-based applications. This architecture is typically front-ended by a web application running in the browser of a desktop or laptop machine. These days, other types of client devices (such as PDAs, cell phones, and telnet devices) are also being used to run these applications. The web application running in a browser or mobile device renders the user interface (data entry screen, Submit button, etc.) using web technologies such as JavaServer Pages (JSP), JavaServer Faces (JSF), or Java Servlets. Typical user actions, such as entering search criteria or adding items to a shopping cart, will invoke/call session beans running in an EJB container via one of the aforementioned web technologies. Once the session beans get invoked, they process the requests, and responses are sent back.

patent database for abstracts containing the term voice and the term identification returns 246 patents A search for speaker and identification in the abstract narrows the number of patents down to 62 Among these include several Japanese patents issued in the late 1970s and into the 1980s, notably one issued to Matsimi Suzuki of Fuji Xerox Company in 1977 entitled Method for verifying identity or difference by voice 12 While the author is not a patent lawyer, this appears to be the first description of an automated electronic system to compare characteristic parameters of an individual s voice for the purpose of verifying identity The increase in the use of cellular phones and the surge of the telecommunications industry in general has produced a number of speaker recognition vendors.

Transformative Paradoxical Challenge What paradoxes have you observed in the learner Select the most significant one. How would you phrase this paradoxical challenge

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