Research And Design Of Small Vocabulary And Speaker-independent Isolated Words Speech Recognition System

Speech Recognition is a branch of voice signal processing technology, through the process of identifying and understanding the voice signal speech recognition make its into the appropriate text or order. Speech Recognition is an interdisciplinary, involving artificial intelligence, pattern recognition, digital signal processing, computer science, language acoustics, psychology, physiology and cognitive science, and many other fields. As an interdisciplinary field, speechr ecognitionist heoretically very valued. Speech recognition has become one of the important research fields and a mark of the development of science. Although speech technology has got some achievements, most speech recognition systems are still limited in lab and would have problems if migrated from lab which are much far from practicality. How to achieve online unsupervised learning methods and more integrated adaptive learning algorithm is the hotspots of current research of speech recognition technology. The ultimate reasons for restricting practicality can be classified to two kinds, one is precision for recognition and the other is complexity of the system.Speech Recognition in accordance with the different tasks can be divided into four areas: speaker recognition, keyword detection, language identification and continuous speech recognition. This paper mainly focuscs on speaker independent isolated word speech recognition algorithm.Fundamentals of speech recognition and its algorithm have been studied in this paper. We compare the difference of the speaker independent isolated word speech recognition algorithm, and select some effective approaches for our system. Then we research on how to realize our speaker independent isolated word recognition algorithm on person computer. The algorithm was realized by Visual C++ in computer finally. The DTW (Dynamic Time Warping) model, which is typically algorithm, is recognition often used in independent small vocabularies speech systems. In this paper, an innovative endpoint detection technology for robust speech recognition is presented, according to the voice data information, this technology, based on the traditional zero-rate and short-term energy endpoint detection methods which is called dual-threshold endpoint detection methods, automatically adjust the threshold variable threshold. We simulate and test the algorithms by Matlab. Tests show that this endpoint detection algorithm improves the certain of accuracy. Then the algorithm was programmed by the VC. In the voice signal acquisition, by calling the API of Windows, to a certain extent, reduce the noise on the voice data. In this speech recognition system, the feature extraction algorithm is linear prediction analysis (LPCC), the pattern matching algorithm is dynamic time warping(DTW) and the construction process of speech corpus by clustering. Finally, the algorithm test results were analyzed in this paper.