914 resultados para Speech Recognition System using LPC
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The research presented in this paper is part of an ongoing investigation into how best to incorporate speech-based input within mobile data collection applications. In our previous work [1], we evaluated the ability of a single speech recognition engine to support accurate, mobile, speech-based data input. Here, we build on our previous research to compare the achievable speaker-independent accuracy rates of a variety of speech recognition engines; we also consider the relative effectiveness of different speech recognition engine and microphone pairings in terms of their ability to support accurate text entry under realistic mobile conditions of use. Our intent is to provide some initial empirical data derived from mobile, user-based evaluations to support technological decisions faced by developers of mobile applications that would benefit from, or require, speech-based data entry facilities.
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Speech recognition technology is regarded as a key enabler for increasing the usability of applications deployed on mobile devices -- devices which are becoming increasingly prevalent in modern hospital-based healthcare. Although the use of speech recognition is not new to the hospital-based healthcare domain, its use with mobile devices has thus far been limited. This paper presents the results of a literature review we conducted in order to observe the manner in which speech recognition technology has been used in hospital-based healthcare and to gain an understanding of how this technology is being evaluated, in terms of its dependability and reliability, in healthcare settings. Our intent is that this review will help identify scope for future uses of speech recognition technologies in the healthcare domain, as well as to identify implications for the meaningful evaluation of such technologies given the specific context of use.
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A high frequency sensing interrogation system by using fiber Bragg grating based microwave photonic filtering is proposed, in which the wavelength measurement sensitivity is proportional to the RF modulation frequency applied to the optical signal.
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We present, for the first time to our knowledge, experimental evidence showing that superimposed blazed fiber Bragg gratings may be fabricated and used to extend the dynamic range of a grating-based spectrometer. Blazed gratings of 4° and 8° were superimposed in germanosilicate fiber by ultraviolet inscription and used in conjunction with a coated charged-coupled device array to interrogate a wavelength-division-multiplexing sensor array. We show that the system can be used to monitor strain and temperature sensors simultaneously with an employable bandwidth which is extendedable to 70 nm.
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Astrocytes are essential for neuronal function and survival, so both cell types were included in a human neurotoxicity test-system to assess the protective effects of astrocytes on neurons, compared with a culture of neurons alone. The human NT2.D1 cell line was differentiated to form either a co-culture of post-mitotic NT2.N neuronal (TUJ1, NF68 and NSE positive) and NT2.A astrocytic (GFAP positive) cells (∼2:1 NT2.A:NT2.N), or an NT2.N mono-culture. Cultures were exposed to human toxins, for 4 h at sub-cytotoxic concentrations, in order to compare levels of compromised cell function and thus evidence of an astrocytic protective effect. Functional endpoints examined included assays for cellular energy (ATP) and glutathione (GSH) levels, generation of hydrogen peroxide (H2O2) and caspase-3 activation. Generally, the NT2.N/A co-culture was more resistant to toxicity, maintaining superior ATP and GSH levels and sustaining smaller significant increases in H2O2 levels compared with neurons alone. However, the pure neuronal culture showed a significantly lower level of caspase activation. These data suggest that besides their support for neurons through maintenance of ATP and GSH and control of H2O2 levels, following exposure to some substances, astrocytes may promote an apoptotic mode of cell death. Thus, it appears the use of astrocytes in an in vitro predictive neurotoxicity test-system may be more relevant to human CNS structure and function than neuronal cells alone. © 2007 Elsevier Ltd. All rights reserved.
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We present a newly designed polymer light-emitting diode with a bandwidth of ∼350 kHz for high-speed visible light communications. Using this new polymer light-emitting diode as a transmitter, we have achieved a record transmission speed of 10 Mb/s for a polymer light-emitting diode-based optical communication system with an orthogonal frequency division multiplexing technique, matching the performance of single carrier formats using multitap equalization. For achieving such a high data-rate, a power pre-emphasis technique was adopted. © 2014 Optical Society of America.
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In this paper we experimentally demonstrate a 10 Mb/s error free visible light communications (VLC) system using polymer light-emitting diodes (PLEDs) for the first time. The PLED under test is a blue emitter with ∼600 kHz bandwidth. Having such a low bandwidth means the introduction of an intersymbol interference (ISI) induced penalty at higher transmission speeds and thus the requirement for an equalizer. In this work we improve on previous literature by implementing a decision feedback equalizer, rather than a linear equalizer. Considering 7% and 20% forward error correction codes, transmission speeds up to ∼12 Mb/s can be supported.
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We present a compact, portable and low cost generic interrogation strain sensor system using a fibre Bragg grating configured in transmission mode with a vertical-cavity surface-emitting laser (VCSEL) light source and a GaAs photodetector embedded in a polymer skin. The photocurrent value is read and stored by a microcontroller. In addition, the photocurrent data is sent via Bluetooth to a computer or tablet device that can present the live data in a real time graph. With a matched grating and VCSEL, the system is able to automatically scan and lock the VCSEL to the most sensitive edge of the grating. Commercially available VCSEL and photodetector chips are thinned down to 20 µm and integrated in an ultra-thin flexible optical foil using several thin film deposition steps. A dedicated micro mirror plug is fabricated to couple the driving optoelectronics to the fibre sensors. The resulting optoelectronic package can be embedded in a thin, planar sensing sheet and the host material for this sheet is a flexible and stretchable polymer. The result is a fully embedded fibre sensing system - a photonic skin. Further investigations are currently being carried out to determine the stability and robustness of the embedded optoelectronic components. © 2012 Copyright Society of Photo-Optical Instrumentation Engineers (SPIE).
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In this paper, we report a simple fibre laser torsion sensor system using an intracavity tilted fibre grating as a torsion encoded loss filter. When the grating is subjected to twist, it induces loss to the cavity, thus affecting the laser oscillation build-up time. By measuring the build-up time, both twist direction and angle on the grating can be monitored. Using a low-cost photodiode and a two-channel digital oscilloscope, we have characterised the torsion sensing capability of this fibre laser system and obtained a torsion sensitivity of ~412µs/(rad/m) in the dynamic range from -150° to +150°.
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We present the compensation of the equalization enhanced phase noise (EEPN) in the long-haul n-level phase shift keying (n-PSK) coherent optical transmission system, by employing a scheme of phase modulated optical pilot carrier. © OSA 2013.
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A highly sensitive liquid level monitoring system based on microstructured polymer optical fiber Bragg grating (mPOFBG) array sensors is reported for the first time. The configuration is based on five mPOFBGs inscribed in the same fiber in the 850 nm spectral region, showing the potential to interrogate liquid level by measuring the strain induced in each mPOFBG embedded in a silicone rubber (SR) diaphragm, which deforms due to hydrostatic pressure variations. The sensor exhibits a highly linear response over the sensing range, a good repeatability, and a high resolution. The sensitivity of the sensor is found to be 98 pm/cm of water, enhanced by more than a factor of 9 when compared to an equivalent sensor based on a silica fiber around 1550 nm. The temperature sensitivity is studied and a multi-sensor arrangement proposed, which has the potential to provide level readings independent of temperature and the liquid density.
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Real-time small angle neutron scattering and wide angle neutron scattering studies were undertaken concurrently on a glass ionomer of nominal composition 4.5(SiO2)-3(Al2O3)-1.5(P2O5)-3(CaO)-2(CaF2). Neutron studies were conducted as a function of temperature to investigate the crystallisation process. No amorphous phase separation was observed at room temperature and the onset of crystallisation was found to occur at 650°C, which is 90°C lower than previously reported. The first crystalline phase observed corresponded to fluorapatite; it was only upon further heating was the mullite phase became present. The crystallite size at 650°C was found to be ~115Å and the result was consistent across all measurements.
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Three new technologies have been brought together to develop a miniaturized radiation monitoring system. The research involved (1) Investigation a new HgI$\sb2$ detector. (2) VHDL modeling. (3) FPGA implementation. (4) In-circuit Verification. The packages used included an EG&G's crystal(HgI$\sb2$) manufactured at zero gravity, the Viewlogic's VHDL and Synthesis, Xilinx's technology library, its FPGA implementation tool, and a high density device (XC4003A). The results show: (1) Reduced cycle-time between Design and Hardware implementation; (2) Unlimited Re-design and implementation using the static RAM technology; (3) Customer based design, verification, and system construction; (4) Well suited for intelligent systems. These advantages excelled conventional chip design technologies and methods in easiness, short cycle time, and price in medium sized VLSI applications. It is also expected that the density of these devices will improve radically in the near future. ^
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The need to incorporate advanced engineering tools in biology, biochemistry and medicine is in great demand. Many of the existing instruments and tools are usually expensive and require special facilities.^ With the advent of nanotechnology in the past decade, new approaches to develop devices and tools have been generated by academia and industry. ^ One such technology, NMR spectroscopy, has been used by biochemists for more than 2 decades to study the molecular structure of chemical compounds. However, NMR spectrometers are very expensive and require special laboratory rooms for their proper operation. High magnetic fields with strengths in the order of several Tesla make these instruments unaffordable to most research groups.^ This doctoral research proposes a new technology to develop NMR spectrometers that can operate at field strengths of less than 0.5 Tesla using an inexpensive permanent magnet and spin dependent nanoscale magnetic devices. This portable NMR system is intended to analyze samples as small as a few nanoliters.^ The main problem to resolve when downscaling the variables is to obtain an NMR signal with high Signal-To-Noise-Ratio (SNR). A special Tunneling Magneto-Resistive (TMR) sensor design was developed to achieve this goal. The minimum specifications for each component of the proposed NMR system were established. A complete NMR system was designed based on these minimum requirements. The goat was always to find cost effective realistic components. The novel design of the NMR system uses technologies such as Direct Digital Synthesis (DDS), Digital Signal Processing (DSP) and a special Backpropagation Neural Network that finds the best match of the NMR spectrum. The system was designed, calculated and simulated with excellent results.^ In addition, a general method to design TMR Sensors was developed. The technique was automated and a computer program was written to help the designer perform this task interactively.^
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This dissertation introduces a new system for handwritten text recognition based on an improved neural network design. Most of the existing neural networks treat mean square error function as the standard error function. The system as proposed in this dissertation utilizes the mean quartic error function, where the third and fourth derivatives are non-zero. Consequently, many improvements on the training methods were achieved. The training results are carefully assessed before and after the update. To evaluate the performance of a training system, there are three essential factors to be considered, and they are from high to low importance priority: (1) error rate on testing set, (2) processing time needed to recognize a segmented character and (3) the total training time and subsequently the total testing time. It is observed that bounded training methods accelerate the training process, while semi-third order training methods, next-minimal training methods, and preprocessing operations reduce the error rate on the testing set. Empirical observations suggest that two combinations of training methods are needed for different case character recognition. Since character segmentation is required for word and sentence recognition, this dissertation provides also an effective rule-based segmentation method, which is different from the conventional adaptive segmentation methods. Dictionary-based correction is utilized to correct mistakes resulting from the recognition and segmentation phases. The integration of the segmentation methods with the handwritten character recognition algorithm yielded an accuracy of 92% for lower case characters and 97% for upper case characters. In the testing phase, the database consists of 20,000 handwritten characters, with 10,000 for each case. The testing phase on the recognition 10,000 handwritten characters required 8.5 seconds in processing time.