Speech Processing Using Artificial Neural Networks
نویسندگان
چکیده
A three layer perceptron network is used to classify the /i/ sound using isolated words from diierent speakers. A classiication accuracy of 97% has been achieved. A map of phonemes is used to trace trajectories of utterances using the self-organising neural network. A crinkle factor is proposed which allows using the self-organising map to determine the inherent dimensionality of a set of points. By this technique speech data has been shown to possess an inherent dimensionality of at least four. A projection of the map and the speech data shows how the self-organising map ts the speech space.
منابع مشابه
Damage detection and structural health monitoring of ST-37 plate using smart materials and signal processing by artificial neural networks
Structural health monitoring (SHM) systems operate online and test different materials using ultrasonic guided waves and piezoelectric smart materials. These systems are permanently installed on the structures and display information on the monitor screen. The user informs the engineers of the existing damage after observing signal loss which appears after damage is caused. In this paper health...
متن کاملPersian Phone Recognition Using Acoustic Landmarks and Neural Network-based variability compensation methods
Speech recognition is a subfield of artificial intelligence that develops technologies to convert speech utterance into transcription. So far, various methods such as hidden Markov models and artificial neural networks have been used to develop speech recognition systems. In most of these systems, the speech signal frames are processed uniformly, while the information is not evenly distributed ...
متن کاملCurl Size and Pelt Color Determination of Zandi Lambs Using Image Processing and Artificial Neural Network
In this study, a method based on using image processing and artificial neural network is introduced to determine pelt color and curl size of newborn lambs in Zandi sheep. The data was collected from 300 newborn lambs reared in the Zandi sheep breeding centre of Khojir, Tehran. Primarily, curl size and pelt color of new born lambs was recorded by experienced appraisers, and at the same time, sev...
متن کاملPrediction of the changes in physicochemical properties of key lime juice during IR thermal processing by artificial neural networks
Thermal processing of the key lime juice leads to the inactivation of pectin methylesterase (PME) and the degradation of ascorbic acid (AA). These changes affect directly the cloud stability and color of the juice. In this study, an artificial neural network (ANN) model was applied for designing and developing an intelligent system for prediction of the thermal processing effects on the physico...
متن کاملIntegration of Color Features and Artificial Neural Networks for In-field Recognition of Saffron Flower
ABSTRACT-Manual harvesting of saffron as a laborious and exhausting job; it not only raises production costs, but also reduces the quality due to contaminations. Saffron quality could be enhanced if automated harvesting is substituted. As the main step towards designing a saffron harvester robot, an appropriate algorithm was developed in this study based on image processing techniques to recogn...
متن کاملPrediction of breeding values for the milk production trait in Iranian Holstein cows applying artificial neural networks
The artificial neural networks, the learning algorithms and mathematical models mimicking the information processing ability of human brain can be used non-linear and complex data. The aim of this study was to predict the breeding values for milk production trait in Iranian Holstein cows applying artificial neural networks. Data on 35167 Iranian Holstein cows recorded between 1998 to 2009 were ...
متن کامل