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Showing 1 to 20 of 183 for “"Recognition systems"”.

  1. Improving multilingual speech recognition systems

    Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2022-04-06 without embargo terms

    uiuc Repository record for Improving multilingual speech recognition systems (opens in a new tab)

  2. Document Layout Analysis and Recognition Systems

    … domain-specific questions from Optical Character Recognition (OCR) documents is critical for developing intelligent systems, such as document search engines, sentiment analysis, and information retrieval, since hands-on knowledge extraction by a domain expert with a large volume of documents is …

    kennesaw Repository record for Document Layout Analysis and Recognition Systems (opens in a new tab)

  3. Classifiers : adaptive modules in pattern recognition systems

    Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 1989.

    mit Repository record for Classifiers : adaptive modules in pattern recognition systems (opens in a new tab)

  4. Synthetic recognition systems : self-assembly and metal chelation

    Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Chemistry, 1994.

    mit Repository record for Synthetic recognition systems : self-assembly and metal chelation (opens in a new tab)

  5. An architecture for low-power voice-command recognition systems

    … features and are implemented in large scale systems where power and other resources are abundant. With emerging interest in embedded applications, nano-scale systems, and mobile devices, which are power and computation constrained, there is a rising need to find simple, low-power solutions …

    mit Repository record for An architecture for low-power voice-command recognition systems (opens in a new tab)

  6. Neural Time Alignment for End-to-End Automatic Speech Recognition Systems

    Automatic Speech Recognition (ASR) is an important component for machines to interact with humans. With the development of deep learning, ASR systems can obtain very low error rates when there is a lot of training data available. Apart from the recognised text, it is also important to determine …

    cambridge Repository record for Neural Time Alignment for End-to-End Automatic Speech Recognition Systems (opens in a new tab)

  7. Transformation Tolerance and Demographic Robustness of Machine-based Face Recognition Systems

    Face recognition is widely acknowledged to be a very complex visual task for both humans and computers. Previous studies which analyze robustness of facial recognition systems have revealed that the ability to recognize faces becomes worse as the blur levels of face images increases, and that …

    mit Repository record for Transformation Tolerance and Demographic Robustness of Machine-based Face Recognition Systems (opens in a new tab)

  8. Error propagation in pattern recognition systems: Impact of quality on fingerprint categorization

    … of biometric identification and authentication systems. The results presented in the literature indicate that incorporating information about quality of the input pattern leads to improved classification performance. The quality itself, however, can be defined in a number of ways, and its role …

    unh-thes Repository record for Error propagation in pattern recognition systems: Impact of quality on fingerprint categorization (opens in a new tab)

  9. Text-image Restoration And Text Alignment For Multi-engine Optical Character Recognition Systems

    … that combining three different optical character recognition (OCR) engines (ExperVision® OCR, Scansoft OCR, and Abbyy® OCR) results using voting algorithms will get higher accuracy rate than each of the engines individually. While a voting algorithm has been realized, several aspects to …

    ucf

  10. Joint Training Methods for Tandem and Hybrid Speech Recognition Systems using Deep Neural Networks

    … approach for state-of-the-art automatic speech recognition (ASR) systems over the past few decades. Recently, due to the rapid development of deep learning technologies, deep neural networks (DNNs) have become an essential part of nearly all kinds of ASR approaches. Among HMM-based ASR …

    cambridge Repository record for Joint Training Methods for Tandem and Hybrid Speech Recognition Systems using Deep Neural Networks (opens in a new tab)

  11. A comparison of the network speech recognition and distributed speech recognition systems and their effect on speech enabling mobile devices

    Over the past 10 years there has been an exponential increase in the number of mobile subscribers worldwide. Market research has shown that the number of mobile subscribers rose to 4.3 billion towards end of Q1 in 2009. The unprecedented development of the telecommunication industry over the last …

    cape-town Repository record for A comparison of the network speech recognition and distributed speech recognition systems and their effect on speech enabling mobile devices (opens in a new tab)

  12. Pattern recognition and the nondeterminable affine parameter problem

    … reports on the process of implementing pattern recognition systems using classification models such as artificial neural networks (ANNs) and algorithms whose theoretical foundations come from statistics. The issues involved in implementing several classification models and pre-processing …

    cape-town Repository record for Pattern recognition and the nondeterminable affine parameter problem (opens in a new tab)

  13. Using a low-bit rate speech enhancement variable post-filter as a speech recognition system pre-filter to improve robustness to GSM speech

    Performance of speech recognition systems degrades when they are used to recognize speech that has been transmitted through GS1 (Global System for Mobile Communications) voice communication channels (GSM speech). This degradation is mainly due to GSM speech coding and GSM channel noise on speech …

    cape-town Repository record for Using a low-bit rate speech enhancement variable post-filter as a speech recognition system pre-filter to improve robustness to GSM speech (opens in a new tab)

  14. Low-complexity convolutional neural networks for automatic target recognition

    … been proposed for designing automatic target recognition systems based on synthetic aperture radar imagery. Recently, with the rise of Deep Learning, there has been growing interest in developing neural network based automatic target recognition systems for synthetic aperture radar …

    uiuc Repository record for Low-complexity convolutional neural networks for automatic target recognition (opens in a new tab)

  15. Implementation and evaluation of a low complexity microphone array for speaker recognition

    … for improving the robustness of speaker recognition systems in a diffuse noise field.

    cape-town Repository record for Implementation and evaluation of a low complexity microphone array for speaker recognition (opens in a new tab)

  16. Feature Selection Using Genetic Algorithms for Human Gait Recognition

    … the importance of feature selection in gait recognition systems. Feature selection is an important factor which impacts the classification accuracy. This goal is achieved by discarding irrelevant and redundant information which affects both the classifier's performance and system's …

    unr Repository record for Feature Selection Using Genetic Algorithms for Human Gait Recognition (opens in a new tab)

  17. Do In-Vehicle Systems Utilizing Voice-Recognition Technology Impact Driving Performance? A Systematic Review and Meta-Analysis

    … with or capable of supporting hands-free systems that use voice-recognition technology. Although voice-recognition technology is viewed favourably among the public, it is not clear whether these systems should be considered safe alternatives to traditional handheld phones and visual-manual …

    calgary Repository record for Do In-Vehicle Systems Utilizing Voice-Recognition Technology Impact Driving Performance? A Systematic Review and Meta-Analysis (opens in a new tab)

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