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At least 163 records · Page 9

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NASA NTRS1988

Real-time speech encoding based on Code-Excited Linear Prediction (CELP)

This paper reports on the work proceeding with regard to the development of a real-time voice codec for the terrestrial and satellite mobile radio environments. The codec is based on a complexity reduced version of code-excited linear prediction (CELP). The codebook search complexity was reduced to only 0.5 million floating point operations per second (MFLOPS) while maintaining excellent speech quality. Novel methods to quantize the residual and the long and short term model filters are presented.

Leblanc, Wilfrid P.↗

NASA NTRS1990

Automatic speech recognition in air traffic control

Automatic Speech Recognition (ASR) technology and its application to the Air Traffic Control system are described. The advantages of applying ASR to Air Traffic Control, as well as criteria for choosing a suitable ASR system are presented. Results from previous research and directions for future work at the Flight Transportation Laboratory are outlined.

Karlsson, Joakim↗

NASA NTRS1989

Automatic speech recognition in air-ground data link

In the present air traffic system, information presented to the transport aircraft cockpit crew may originate from a variety of sources and may be presented to the crew in visual or aural form, either through cockpit instrument displays or, most often, through voice communication. Voice radio communications are the most error prone method for air-ground data link. Voice messages can be misstated or misunderstood and radio frequency congestion can delay or obscure important messages. To prevent proliferation, a multiplexed data link display can be designed to present information from multiple data link sources on a shared cockpit display unit (CDU) or multi-function display (MFD) or some future combination of flight management and data link information. An aural data link which incorporates an automatic speech recognition (ASR) system for crew response offers several advantages over visual displays. The possibility of applying ASR to the air-ground data link was investigated. The first step was to review current efforts in ASR applications in the cockpit and in air traffic control and evaluated their possible data line application. Next, a series of preliminary research questions is to be developed for possible future collaboration.

Armstrong, Herbert B.↗

NASA NTRS1990

Automatic Speech Recognition in Air Traffic Control: a Human Factors Perspective

The introduction of Automatic Speech Recognition (ASR) technology into the Air Traffic Control (ATC) system has the potential to improve overall safety and efficiency. However, because ASR technology is inherently a part of the man-machine interface between the user and the system, the human factors issues involved must be addressed. Here, some of the human factors problems are identified and related methods of investigation are presented. Research at M.I.T.'s Flight Transportation Laboratory is being conducted from a human factors perspective, focusing on intelligent parser design, presentation of feedback, error correction strategy design, and optimal choice of input modalities.

Karlsson, Joakim↗

NASA NTRS1990

An empirical investigation of sparse distributed memory using discrete speech recognition

Presented here is a step by step analysis of how the basic Sparse Distributed Memory (SDM) model can be modified to enhance its generalization capabilities for classification tasks. Data is taken from speech generated by a single talker. Experiments are used to investigate the theory of associative memories and the question of generalization from specific instances.

Danforth, Douglas G.↗

NASA NTRS1990

Masking of errors in transmission of VAPC-coded speech

A subjective evaluation is provided of the bit error sensitivity of the message elements of a Vector Adaptive Predictive (VAPC) speech coder, along with an indication of the amenability of these elements to a popular error masking strategy (cross frame hold over). As expected, a wide range of bit error sensitivity was observed. The most sensitive message components were the short term spectral information and the most significant bits of the pitch and gain indices. The cross frame hold over strategy was found to be useful for pitch and gain information, but it was not beneficial for the spectral information unless severe corruption had occurred.

Cox, Neil B.↗

NASA NTRS1977

Multi-system approach to speech understanding

The Harpy and Hearsay-2 systems are described. The performance of these systems was tabulated. The large number of design decisions which confront a speech understanding system are discussed.

Reddy, Raj↗

NASA NTRS1977

Automatic speech recognition research at NASA-Ames Research Center

A trainable acoustic pattern recognizer manufactured by Scope Electronics is presented. The voice command system VCS encodes speech by sampling 16 bandpass filters with center frequencies in the range from 200 to 5000 Hz. Variations in speaking rate are compensated for by a compression algorithm that subdivides each utterance into eight subintervals in such a way that the amount of spectral change within each subinterval is the same. The recorded filter values within each subinterval are then reduced to a 15-bit representation, giving a 120-bit encoding for each utterance. The VCS incorporates a simple recognition algorithm that utilizes five training samples of each word in a vocabulary of up to 24 words. The recognition rate of approximately 85 percent correct for untrained speakers and 94 percent correct for trained speakers was not considered adequate for flight systems use. Therefore, the built-in recognition algorithm was disabled, and the VCS was modified to transmit 120-bit encodings to an external computer for recognition.

Coler, Clayton R.↗

NASA NTRS1988

President Kennedy's Speech at Rice University

Unedited film footage of President John F. Kennedy's speech at Rice University, Houston, Texas, September 12, 1962. Includes the following quote: "We choose to go to the Moon in this decade, and do the other things, not because they are easy, but because they are hard. Because that goal will serve to organize and measure the best of our energies and skills. Because that challenge is one that we are willing to accept, one we are unwilling to postpone, and one we intend to win.”

Source record↗

NASA NTRS1994

Application of the wavelet transform for speech processing

Speaker identification and word spotting will shortly play a key role in space applications. An approach based on the wavelet transform is presented that, in the context of the 'modulation model,' enables extraction of speech features which are used as input for the classification process.

Maes, Stephane↗

NASA NTRS1995

Index to NASA news releases and speeches 1994

This index contains a listing of news releases distributed by the Office of Public Affairs, NASA Headquarters, and a selected listing of speeches presented by members of the Headquarters staff during 1994.

Source record↗

NASA NTRS1993

Embedding speech into virtual realities

In this work a speaker-independent speech recognition system is presented, which is suitable for implementation in Virtual Reality applications. The use of an artificial neural network in connection with a special compression of the acoustic input leads to a system, which is robust, fast, easy to use and needs no additional hardware, beside a common VR-equipment.

Bohn, Christian-Arved↗

NASA NTRS1998

Real-Time Reconfigurable Adaptive Speech Recognition Command and Control Apparatus and Method

An adaptive speech recognition and control system and method for controlling various mechanisms and systems in response to spoken instructions and in which spoken commands are effective to direct the system into appropriate memory nodes, and to respective appropriate memory templates corresponding to the voiced command is discussed. Spoken commands from any of a group of operators for which the system is trained may be identified, and voice templates are updated as required in response to changes in pronunciation and voice characteristics over time of any of the operators for which the system is trained. Provisions are made for both near-real-time retraining of the system with respect to individual terms which are determined not be positively identified, and for an overall system training and updating process in which recognition of each command and vocabulary term is checked, and in which the memory templates are retrained if necessary for respective commands or vocabulary terms with respect to an operator currently using the system. In one embodiment, the system includes input circuitry connected to a microphone and including signal processing and control sections for sensing the level of vocabulary recognition over a given period and, if recognition performance falls below a given level, processing audio-derived signals for enhancing recognition performance of the system.

Salazar, George A.↗

NASA NTRS2003

Subauditory Speech Recognition based on EMG/EPG Signals

Sub-vocal electromyogram/electro palatogram (EMG/EPG) signal classification is demonstrated as a method for silent speech recognition. Recorded electrode signals from the larynx and sublingual areas below the jaw are noise filtered and transformed into features using complex dual quad tree wavelet transforms. Feature sets for six sub-vocally pronounced words are trained using a trust region scaled conjugate gradient neural network. Real time signals for previously unseen patterns are classified into categories suitable for primitive control of graphic objects. Feature construction, recognition accuracy and an approach for extension of the technique to a variety of real world application areas are presented.

Jorgensen, Charles↗

NASA NTRS1989

Vector excitation speech or audio coder for transmission or storage

A vector excitation coder compresses vectors by using an optimum codebook designed off line, using an initial arbitrary codebook and a set of speech training vectors exploiting codevector sparsity (i.e., by making zero all but a selected number of samples of lowest amplitude in each of N codebook vectors). A fast-search method selects a number N.sub.c of good excitation vectors from the codebook, where N.sub.c is much smaller tha ORIGIN OF INVENTION The invention described herein was made in the performance of work under a NASA contract, and is subject to the provisions of Public Law 96-517 (35 USC 202) under which the inventors were granted a request to retain title.

Davidson, Grant↗

NASA NTRS2008

Leadership in Space: Selected Speeches of NASA Administrator Michael Griffin, May 2005 - October 2008

Speech topics include: Leadership in Space; Space Exploration: Real and Acceptable Reasons; Why Explore Space?; Space Exploration: Filling up the Canvas; Continuing the Voyage: The Spirit of Endeavour; Incorporating Space into Our Economic Sphere of Influence; The Role of Space Exploration in the Global Economy; Partnership in Space Activities; International Space Cooperation; National Strategy and the Civil Space Program; What the Hubble Space Telescope Teaches Us about Ourselves; The Rocket Team; NASA's Direction; Science and NASA; Science Priorities and Program Management; NASA and the Commercial Space Industry; NASA and the Business of Space; American Competitiveness: NASA's Role & Everyone's Responsibility; Space Exploration: A Frontier for American Collaboration; The Next Generation of Engineers; System Engineering and the "Two Cultures" of Engineering; Generalship of Engineering; NASA and Engineering Integrity; The Constellation Architecture; Then and Now: Fifty Years in Space; The Reality of Tomorrow; and Human Space Exploration: The Next 50 Years.

Griffin, Michael↗

NASA NTRS2009

Applications of sub-audible speech recognition based upon electromyographic signals

Method and system for generating electromyographic or sub-audible signals (''SAWPs'') and for transmitting and recognizing the SAWPs that represent the original words and/or phrases. The SAWPs may be generated in an environment that interferes excessively with normal speech or that requires stealth communications, and may be transmitted using encoded, enciphered or otherwise transformed signals that are less subject to signal distortion or degradation in the ambient environment.

Jorgensen, C. Charles↗

NASA NTRSDate not supplied

Natural Language Processing Methods for Air Traffic Management Text and Speech Data

This presentation discusses two efforts of the NARI AI/ML Intern team during the Fall 2021 OSTEM Internship term. For Letters of Agreement (LoA), we have studied how LoAs are structured and explored the question ‘What is an LoA constraint?’ To do this, our approach is data-driven, iterative, and assisted by machine learning when available. In this presentation, we will walk through our tasks of manually scanning through documents, performing a preliminary entity labelling task, and our unsupervised analysis on LoA procedures sections. After this research phase, we define the smallest constraint unit in an LoA, and start to perform entity extraction. Looking towards constraint extraction, we are also exploring the use of a one-class support vector machine (OneClassSVM) model to identify patterns within the data. The second effort of our team this term is focused on Air Traffic Control System Command Center (ATCSCC) advisory meetings, and the subsequent advisory documents that get published from their content. These advisory documents are important to give readily accessible summaries of daily operations, so that data centers, airline officials, and other stakeholders can easily understand the context of these meetings in real time. In applying machine learning to this scenario, two natural language processing tasks are used. First is developing machine learning models to convert the meeting speech data into text. With this text, use of extractive and abstractive text summarization models are used to automatically generate preliminary versions of the advisory documents.

Natural Language Processing↗