Introduction

1. A traditional calculator is a small electronic device used to perform the basic operations of arithmetic. The drawbacks are complicated button organization, user-unfriendly display screen and lack of functional features that are frequently used in daily life. According to our research, we found that we could modify the traditional calculator and build a new prototype of computational tool. In our project, we employed speech recognition and text-to-speech that are rarely put together in use. Current speech recognition applications are usually built in Java using Sphinx4. The language models are built particularly according to functionality. However, there is no language model so far designed for computational problems. We designed such a model and built of prototype software that has user-friendly interface, and useful functional features including multi-step calculation, unit/currency conversion and background processing features. We developed a new software equipped with voice recognition system. It is capable of solving simple computational problems with multi-step calculation, unit/currency conversion and background processing features. We had introduce our product to our fellow students, and received positive feedback. Introduction Methods Preparing ( – April 26th): We designed and conducted the Wizard-of-Oz experiment. This experiment aimed to simulate the user-computer interaction and increase the size of existing dictionary. During the experiment, we took each participant to a separate room, and let them ask the computer several questions. Meanwhile, one of us usedWolfram Alpha to give answers, and recorded the entire conversation in a log file. After each experiment, we also collected demographic information of the participant. Programming(April 27th – May 3rd): Once we had collected enough information, we organized the results and improved our dictionary at the beginning of the week. We could then study Sphinx 4 and text-to-speech, and combined them with the processing part we had already programmed. We would examine the effectiveness and efficiency of our program, and make changes accordingly if needed. Testing and Improving(May 4th – May 10th): The prototype was ready at the beginning of the week. We continued to improve our prototype by getting rid of bugs in the program and adding features that enhanced the usability and differentiate our final product. We prepared for the presentation and demonstration in the last class. Time Line The following exhibits our progress during this project. The first two figures show two prototypes, one in C# using Windows Speech Recognition System, the other in Java using Sphinx4. Figure three and four present the interface of our final product. Result Demonstration Reference Acknowledgement We would like to thank Professor. Nikolaos and Professor Leonard for the instructions during this semester. A special thanks to George for great help on our project! Background research: Speech recognition / Speech synthesis Wizard-of-Oz experiment: Nearly 100 participants Programming the prototype: In C# using speech system of Windows. In JAVA using Sphinx 4 Building language model: CMU-Cam Statistical Language Modeling Toolkit, word frequency, vocabulary, simple - Ngram model Making grammar file: six types of expression. Weight – Probability Cutoff Testing and further improvement: Memory (Multi-step calculation) Unit conversion/ Currency conversion Background priority Professor Nikolaos Professor Leonard George Haoran Liang Xiaohua Liu Conversational Calculator Knuth, Donald E. (1964). "Backus Normal Form vs. Backus Naur Form". Communications of the ACM7 (12): 735–736. Kelley, J.F., “CAL – A Natural Language program developed with the OZ Paradigm: Implications for Supercomputing Systems”. First International Conference on Supercomputing Systems (St. Petersburg, Florida, 16–20 December 1985), New York: ACM, pp. 238–248 YuanhuaLv and ChengXiangZhai, Positional Language Models for Information Retrieval, in Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval (SIGIR), 2009. Figure one in Microsoft Visual Studio Figure two in Netbeans Figure three memory features Figure four conversion features