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At least 127 records · Page 7

All sources NASA NTRS DOE OSTI

NASA NTRS2010

NASA Tech Briefs, November 2010

Topics covered include: Portable Handheld Optical Window Inspection Device; Salience Assignment for Multiple-Instance Data and Its Application to Crop Yield Prediction; Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems ; Predicting Long-Range Traversability from Short-Range Stereo-Derived Geometry; Browser-Based Application for Telemetry Monitoring of Robotic Assets; Miniature Low-Noise G-Band I-Q Receiver; Methods of Using a Magnetic Field Response Sensor Within Closed, Electrically Conductive Containers; Differential Resonant Ring YIG Tuned Oscillator; Microfabricated Segmented-Involute-Foil Regenerator for Stirling Engines; Reducing Seal Adhesion in Low Impact Docking Systems; Optimal Flow Control Design; Corrosion-Resistant Container for Molten-Material Processing; Reusable Hot-Wire Cable Cutter; Deployment of a Curved Truss; High-Volume Airborne Fluids Handling Technologies to Fight Wildfires; Modeling of Alkane Oxidation Using Constituents and Species; Fabrication of Lanthanum Telluride 14-1-11 Zintl High-Temperature Thermoelectric Couple; A Computer Model for Analyzing Volatile Removal Assembly; Analysis of Nozzle Jet Plume Effects on Sonic Boom Signature; Optical Sidebands Multiplier; Single Spatial-Mode Room-Temperature-Operated 3.0 to 3.4 micrometer Diode Lasers; Self-Nulling Beam Combiner Using No External Phase Inverter; Portable Dew Point Mass Spectrometry System for Real-Time Gas and Moisture Analysis; Maximum Likelihood Time-of-Arrival Estimation of Optical Pulses via Photon-Counting Photodetectors; Handheld White Light Interferometer for Measuring Defect Depth in Windows; Decomposition Algorithm for Global Reachability on a Time-Varying Graph; Autonomous GN and C for Spacecraft Exploration of Comets and Asteroids; Efficient Web Services Policy Combination; Using CTX Image Features to Predict HiRISE-Equivalent Rock Density; Isolation of the Paenibacillus phoenicis, a Spore-Forming Bacterium; Monolithically Integrated, Mechanically Resilient Carbon-Based Probes for Scanning Probe Microscopy; Cell Radiation Experiment System; Process to Produce Iron Nanoparticle Lunar Dust Simulant Composite; Inversion Method for Early Detection of ARES-1 Case Breach Failure; Use of ILTV Control Laws for LaNCETS Flight Research;and Evaluating Descent and Ascent Trajectories Near Non-Spherical Bodies.

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NASA NTRS2010

Language Model Combination and Adaptation Using Weighted Finite State Transducers

In speech recognition systems language model (LMs) are often constructed by training and combining multiple n-gram models. They can be either used to represent different genres or tasks found in diverse text sources, or capture stochastic properties of different linguistic symbol sequences, for example, syllables and words. Unsupervised LM adaption may also be used to further improve robustness to varying styles or tasks. When using these techniques, extensive software changes are often required. In this paper an alternative and more general approach based on weighted finite state transducers (WFSTs) is investigated for LM combination and adaptation. As it is entirely based on well-defined WFST operations, minimum change to decoding tools is needed. A wide range of LM combination configurations can be flexibly supported. An efficient on-the-fly WFST decoding algorithm is also proposed. Significant error rate gains of 7.3% relative were obtained on a state-of-the-art broadcast audio recognition task using a history dependently adapted multi-level LM modelling both syllable and word sequences

Liu, X.↗

NASA NTRS2013

Spinoff 2012

Topics covered include: Water Treatment Technologies Inspire Healthy Beverages; Dietary Formulas Fortify Antioxidant Supplements; Rovers Pave the Way for Hospital Robots; Dry Electrodes Facilitate Remote Health Monitoring; Telescope Innovations Improve Speed, Accuracy of Eye Surgery; Superconductors Enable Lower Cost MRI Systems; Anti-Icing Formulas Prevent Train Delays; Shuttle Repair Tools Automate Vehicle Maintenance; Pressure-Sensitive Paints Advance Rotorcraft Design Testing; Speech Recognition Interfaces Improve Flight Safety; Polymers Advance Heat Management Materials for Vehicles; Wireless Sensors Pinpoint Rotorcraft Troubles; Ultrasonic Detectors Safely Identify Dangerous, Costly Leaks; Detectors Ensure Function, Safety of Aircraft Wiring; Emergency Systems Save Tens of Thousands of Lives; Oxygen Assessments Ensure Safer Medical Devices; Collaborative Platforms Aid Emergency Decision Making; Space-Inspired Trailers Encourage Exploration on Earth; Ultra-Thin Coatings Beautify Art; Spacesuit Materials Add Comfort to Undergarments; Gigapixel Images Connect Sports Teams with Fans; Satellite Maps Deliver More Realistic Gaming; Elemental Scanning Devices Authenticate Works of Art; Microradiometers Reveal Ocean Health, Climate Change; Sensors Enable Plants to Text Message Farmers; Efficient Cells Cut the Cost of Solar Power; Shuttle Topography Data Inform Solar Power Analysis; Photocatalytic Solutions Create Self-Cleaning Surfaces; Concentrators Enhance Solar Power Systems; Innovative Coatings Potentially Lower Facility Maintenance Costs; Simulation Packages Expand Aircraft Design Options; Web Solutions Inspire Cloud Computing Software; Behavior Prediction Tools Strengthen Nanoelectronics; Power Converters Secure Electronics in Harsh Environments; Diagnostics Tools Identify Faults Prior to Failure; Archiving Innovations Preserve Essential Historical Records; Meter Designs Reduce Operation Costs for Industry; Commercial Platforms Allow Affordable Space Research; Fiber Optics Deliver Real-Time Structural Monitoring; Camera Systems Rapidly Scan Large Structures; Terahertz Lasers Reveal Information for 3D Images; Thin Films Protect Electronics from Heat and Radiation; Interferometers Sharpen Measurements for Better Telescopes; and Vision Systems Illuminate Industrial Processes.

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NASA NTRS2014

NASA Tech Briefs, June 2014

Topics include: Real-Time Minimization of Tracking Error for Aircraft Systems; Detecting an Extreme Minority Class in Hyperspectral Data Using Machine Learning; KSC Spaceport Weather Data Archive; Visualizing Acquisition, Processing, and Network Statistics Through Database Queries; Simulating Data Flow via Multiple Secure Connections; Systems and Services for Near-Real-Time Web Access to NPP Data; CCSDS Telemetry Decoder VHDL Core; Thermal Response of a High-Power Switch to Short Pulses; Solar Panel and System Design to Reduce Heating and Optimize Corridors for Lower-Risk Planetary Aerobraking; Low-Cost, Very Large Diamond-Turned Metal Mirror; Very-High-Load-Capacity Air Bearing Spindle for Large Diamond Turning Machines; Elevated-Temperature, Highly Emissive Coating for Energy Dissipation of Large Surfaces; Catalyst for Treatment and Control of Post-Combustion Emissions; Thermally Activated Crack Healing Mechanism for Metallic Materials; Subsurface Imaging of Nanocomposites; Self-Healing Glass Sealants for Solid Oxide Fuel Cells and Electrolyzer Cells; Micromachined Thermopile Arrays with Novel Thermo - electric Materials; Low-Cost, High-Performance MMOD Shielding; Head-Mounted Display Latency Measurement Rig; Workspace-Safe Operation of a Force- or Impedance-Controlled Robot; Cryogenic Mixing Pump with No Moving Parts; Seal Design Feature for Redundancy Verification; Dexterous Humanoid Robot; Tethered Vehicle Control and Tracking System; Lunar Organic Waste Reformer; Digital Laser Frequency Stabilization via Cavity Locking Employing Low-Frequency Direct Modulation; Deep UV Discharge Lamps in Capillary Quartz Tubes with Light Output Coupled to an Optical Fiber; Speech Acquisition and Automatic Speech Recognition for Integrated Spacesuit Audio Systems, Version II; Advanced Sensor Technology for Algal Biotechnology; High-Speed Spectral Mapper; "Ascent - Commemorating Shuttle" - A NASA Film and Multimedia Project DVD; High-Pressure, Reduced-Kinetics Mechanism for N-Hexadecane Oxidation; Method of Error Floor Mitigation in Low-Density Parity-Check Codes; X-Ray Flaw Size Parameter for POD Studies; Large Eddy Simulation Composition Equations for Two-Phase Fully Multicomponent Turbulent Flows; Scheduling Targeted and Mapping Observations with State, Resource, and Timing Constraints;

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NASA NTRS2016

Using Natural Language to Enhance Mission Effectiveness

The availability of highly capable, yet relatively cheap, unmanned aerial vehicles (UAVs) is opening up new areas of use for hobbyists and for professional-related activities. The driving function of this research is allowing a non-UAV pilot, an operator, to define and manage a mission. This paper describes the preliminary usability measures of an interface that allows an operator to define the mission using speech to make inputs. An experiment was conducted to begin to enumerate the efficacy and user acceptance of using voice commands to define a multi-UAV mission and to provide high-level vehicle control commands such as "takeoff." The primary independent variable was input type - voice or mouse. The primary dependent variables consisted of the correctness of the mission parameter inputs and the time needed to make all inputs. Other dependent variables included NASA-TLX workload ratings and subjective ratings on a final questionnaire. The experiment required each subject to fill in an online form that contained comparable required information that would be needed for a package dispatcher to deliver packages. For each run, subjects typed in a simple numeric code for the package code. They then defined the initial starting position, the delivery location, and the return location using either pull-down menus or voice input. Voice input was accomplished using CMU Sphinx4-5prealpha for speech recognition. They then inputted the length of the package. These were the option fields. The subject had the system "Calculate Trajectory" and then "Takeoff" once the trajectory was calculated. Later, the subject used "Land" to finish the run. After the voice and mouse input blocked runs, subjects completed a NASA-TLX. At the conclusion of all runs, subjects completed a questionnaire asking them about their experience in inputting the mission parameters, and starting and stopping the mission using mouse and voice input. In general, the usability of voice commands is acceptable. With a relatively well-defined and simple vocabulary, the operator can input the vast majority of the mission parameters using simple, intuitive voice commands. However, voice input may be more applicable to initial mission specification rather than for critical commands such as the need to land immediately due to time and feedback constraints. It would also be convenient to retrieve relevant mission information using voice input. Therefore, further on-going research is looking at using intent from operator utterances to provide the relevant mission information to the operator. The information displayed will be inferred from the operator's utterances just before key phrases are spoken. Linguistic analysis of the context of verbal communication provides insight into the intended meaning of commonly heard phrases such as "What's it doing now?" Analyzing the semantic sphere surrounding these common phrases enables us to predict the operator's intent and supply the operator's desired information to the interface. This paper also describes preliminary investigations into the generation of the semantic space of UAV operation and the success at providing information to the interface based on the operator's utterances.

Trujillo, Anna C.↗

NASA NTRS2018

The Next Wave: Humans, Computers, and Redefining Reality

The Augmented/Virtual Reality (AVR) Lab at KSC is dedicated to " exploration into the growing computer fields of Extended Reality and the Natural User Interface (it is) a proving ground for new technologies that can be integrated into future NASA projects and programs." The topics of Human Computer Interface, Human Computer Interaction, Augmented Reality, Virtual Reality, and Mixed Reality are defined; examples of work being done in these fields in the AVR Lab are given. Current new and future work in Computer Vision, Speech Recognition, and Artificial Intelligence are also outlined.

Extended Reality↗

NASA NTRS1981

STS-41 Voice Command System Flight Experiment Report

This report presents the results of the Voice Command System (VCS) flight experiment on the five-day STS-41 mission. Two mission specialists,Bill Shepherd and Bruce Melnick, used the speaker-dependent system to evaluate the operational effectiveness of using voice to control a spacecraft system. In addition, data was gathered to analyze the effects of microgravity on speech recognition performance.

Salazar, George A.↗

NASA NTRS2018

Introduction to NASA Goddard Workshop on Artificial Intelligence

Artificial Intelligence (AI) is a collection of advanced technologies that allows machines to think and act, both humanly and rationally, through sensing, comprehending, acting and learning. AI's foundations lie at the intersection of several traditional fields Philosophy, Mathematics, Economics, Neuroscience, Psychology and Computer Science. Although the inception of AI started in the 1950's, it has recently made a strong comeback in all aspects of society and all over the world; this is mainly due to the timely combination of increased data volumes, advanced and mature algorithms, and improvements in computing power and storage. Current AI applications include big data analytics, robotics, intelligent sensing, assisted decision making, and speech recognition just to name a few.This workshop will be investigating how AI technologies can be adapted or developed to address the following challenges: Discover events of interest and correlations in large amounts of science data; improve the outcomes of science modeling and data assimilation using improved data processing, integration, and analysis. Design advisors for mission planning and operations, including anomaly detection and spacecraft health monitoring. Develop tools for engineering support, including advanced manufacturing, orbit determination, new component design and system engineering. Customize intelligent user interfaces, including visual analytics and natural language processing.

Le Moigne, Jacqueline↗

NASA NTRS2018

Overview of Artificial Intelligence (AI) at NASA Goddard

Le Moigne, Jacqueline↗

NASA NTRSDate not supplied

Autonomy Voice Assistant for NPAS (NASA Platform for Autonomous Systems)

A prototype voice interaction system, Autonomy Voice Assistant (AVA), is described in this paper. AVA is designed to seamlessly integrate into the NASA Platform for Autonomous Systems (NPAS), an autonomy software platform, and to enable an operator to interact with NPAS autonomy applications through voice conversations. By integrating VA with NPAS, a major enhancement to NPAS applications is facilitated, enabling interaction through natural language expressions. An AVA prototype has been designed incorporating two principles:(1) self-containment (no external data or computations required), and (2) a readily modifiable, reconfigurable, and flexible architecture. By using voice messages in an NPAS application, an additional layer of user interface capability is enabled, thereby enhancing a user’s overall experience. Advancements, over the past several decades in speech recognition and natural language processing technologies has made it possible for AVA to implement robust messaging capabilities while still being lightweight. The main objective of incorporating a voice assistant like AVA is to augment the number and effectiveness of interactions a user has with a system that typically uses mouse-based interaction, while simultaneously enriching the user experience and providing heightened system awareness.

Lucian Murdock↗

NASA NTRSDate not supplied

Understanding and Verifying Neural Networks

Deep Neural Networks (DNNs) have gained immense popularity in recent times and have widespread use in applications such as image classification, sentiment analysis, speech recognition and also in safety-critical applications such as autonomous driving. However, they suffer limitations such as lack of explainability and robustness which raise safety and security concerns in their usage. Further, the complex structure and large input spaces of DNNs act as an impediment to thorough verification and testing. The SafeDNN project at the Robust Software Engineering (RSE) group at NASA aims at exploring techniques to ensure that systems that use deep neural networks are safe, robust and interpretable. In this talk, I will be presenting our technique Prophecy that automatically infers formal properties of deep neural network models. The tool extracts patterns based on neuron activations as preconditions that imply certain desirable output properties of the model. I would be highlighting case studies that use Prophecy in obtaining explanations for network decisions, understanding correct and incorrect behavior, providing formal guarantees wrt safety and robustness, and debugging neural network models. We have applied the tool on image classification networks, neural network controllers providing turn advisories in unmanned aircrafts, regression models used for autonomous center-line tracking in aircrafts and neural network object detectors

Deep Neural Networks↗

NASA NTRS2022

Intelligent Response and Interaction System (IRIS) - FY21 Closeout Report

In the second year, the IRIS team developed the components necessary for successful offline deployment of the IRIS services. This includes custom automated speech recognition training on NASA audio data, and in-house development and integration of online and offline conversational services. Lastly, the team worked on integrating the IRIS technology with stakeholders and projects that have a strong need for voice interaction.

Aly Shehata↗

NASA NTRS1985

Speech variability effects on recognition accuracy associated with concurrent task performance by pilots

In the present study of the responses of pairs of pilots to aircraft warning classification tasks using an isolated word, speaker-dependent speech recognition system, the induced stress was manipulated by means of different scoring procedures for the classification task and by the inclusion of a competitive manual control task. Both speech patterns and recognition accuracy were analyzed, and recognition errors were recorded by type for an isolated word speaker-dependent system and by an offline technique for a connected word speaker-dependent system. While errors increased with task loading for the isolated word system, there was no such effect for task loading in the case of the connected word system.

Simpson, C. A.↗

NASA NTRS1972

Speech therapy and voice recognition instrument

Characteristics of electronic circuit for examining variations in vocal excitation for diagnostic purposes and in speech recognition for determiniog voice patterns and pitch changes are described. Operation of the circuit is discussed and circuit diagram is provided.

Cohen, J.↗

DOE OSTI2024

Universal Fourier Attack for Time Series

A wide variety of adversarial attacks have been proposed and explored using image and audio data. These attacks are notoriously easy to generate digitally when the attacker can directly manipulate the input to a model, but are much more difficult to implement in the real world. In this paper we present a universal, time invariant attack for general time series data such that the attack has a frequency spectrum primarily composed of the frequencies present in the original data. The universality of the attack makes it fast and easy to implement as no computation is required to add it to an input, while time invariance is useful for real world deployment. Additionally, the frequency constraint ensures the attack can withstand filtering defenses. We demonstrate the effectiveness of the attack on two different classification tasks through both digital and real world experiments, and show that the attack is robust against common transform-and-compare defense pipelines.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2022

Assessment methods for determining small changes in hearing performance over time

Although the behavioral pure-tone threshold audiogram is considered the gold standard for quantifying hearing loss, assessment of speech understanding, especially in noise, is more relevant to quality of life but is only partly related to the audiogram. Metrics of speech understanding in noise are therefore an attractive target for assessing hearing over time. However, speech-in-noise assessments have more potential sources of variability than pure-tone threshold measures, making it a challenge to obtain results reliable enough to detect small changes in performance. Here, this review examines the benefits and limitations of speech-understanding metrics and their application to longitudinal hearing assessment, and identifies potential sources of variability, including learning effects, differences in item difficulty, and between- and within-individual variations in effort and motivation. We conclude by recommending the integration of non-speech auditory tests, which provide information about aspects of auditory health that have reduced variability and fewer central influences than speech tests, in parallel with the traditional audiogram and speech-based assessments.

60 APPLIED LIFE SCIENCES↗

NASA NTRS1969

A preliminary analysis technique for speech sound classification

Analysis method permitting English speech sound recognition by computer for different speakers

Niederjohn, R. J.↗

NASA NTRS2022

Characterization of Response Times based on Voice Communication and Traffic Surveillance Data

A barrier to the integration of remotely piloted aircraft operations in the U.S. National Airspace System is the latency of voice communications between the air traffic controller and the remote pilot, and the latency of communication between the aircraft and the remote pilot. The latency can be substantial especially when satellite-based beyond-radio-line-of-sight communication and relay through the aircraft are employed. This study uses voice recordings of controller-pilot communications and aircraft track data to establish a baseline of pilot readback latencies and maneuver detection delays in the current piloted operations. A machine learning pipeline was developed to parse the contents of the air traffic control clearances including the callsigns using natural language processing. After manually validating the results obtained using the pipeline, the average pilot readback latency was found to be about 0.6 seconds. The average latency between the end of maneuver (inferred from track data), initiated by the pilot in response to the clearance, and the end of clearance was found to be about 176 seconds for altitude change commands, 69 seconds for heading change commands, and 182 seconds for speed change commands. The average latency between the beginning of maneuver and the end of clearance was found to be about 17 seconds for altitude change commands, 17seconds for heading change commands, and 25 seconds for speed change commands.

controller-pilot communication, communication late↗