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Results for “Speech Acoustics”

Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 19 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1972

Asynchronous sampling of speech with some vocoder experimental results

The method of asynchronously sampling speech is based upon the derivatives of the acoustical speech signal. The following results are apparent from experiments to date: (1) It is possible to represent speech by a string of pulses of uniform amplitude, where the only information contained in the string is the spacing of the pulses in time; (2) the string of pulses may be produced in a simple analog manner; (3) the first derivative of the original speech waveform is the most important for the encoding process; (4) the resulting pulse train can be utilized to control an acoustical signal production system to regenerate the intelligence of the original speech.

Babcock, M. L.↗
DOE OSTI2020

Deep learning approaches for neural decoding across architectures and recording modalities

Decoding behavior, perception or cognitive state directly from neural signals is critical for brain–computer interface research and an important tool for systems neuroscience. In the last decade, deep learning has become the state-of-the-art method in many machine learning tasks ranging from speech recognition to image segmentation. The success of deep networks in other domains has led to a new wave of applications in neuroscience. In this article, we review deep learning approaches to neural decoding. Here, we describe the architectures used for extracting useful features from neural recording modalities ranging from spikes to functional magnetic resonance imaging. Furthermore, we explore how deep learning has been leveraged to predict common outputs including movement, speech and vision, with a focus on how pretrained deep networks can be incorporated as priors for complex decoding targets like acoustic speech or images. Deep learning has been shown to be a useful tool for improving the accuracy and flexibility of neural decoding across a wide range of tasks, and we point out areas for future scientific development.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRS2006

Multimodal Platform Control for Robotic Planetary Exploration Missions

Planetary exploration missions pose unique problems for astronauts seeking to coordinate and control exploration vehicles. These include working in an environment filled with abrasive dust (e.g., regolith compositions), a desire to have effective hands-free communication, and a desire to have effective analog control of robotic platforms or end effectors. Requirements to operate in pressurized suits are particularly problematic due to the increased bulk and stiffness of gloves. As a result, researchers are considering alternative methods to perform fine movement control, for example capitalizing on higher-order voice actuation commands to perform control tasks. This paper presents current research at NASA s Neuro Engineering Laboratory that explores one method-direct bioelectric interpretation-for handling some of these problems. In this type of control system, electromyographic (EMG) signals are used both to facilitate understanding of acoustic speech in pressure-regulated suits 2nd to provide smooth analog control of a robotic platform, all without requiring fine-gained hand movement. This is accomplished through the use of non-invasive silver silver-chloride electrodes located on the forearm, throat, and lower chin, positioned so as to receive electrical activity originating from the muscles during contraction. For direct analog platform control, a small Personal Exploration Rover (PER) built by Carnegie Mellon University Robotics is controlled using forearm contraction duration and magnitudes, measured using several EMG channels. Signal processing is used to translate these signals into directional platform rotation rates and translational velocities. higher order commands were generated by differential contraction patterns called "clench codes."

Jorgensen, Charles↗
NASA NTRS2015

Speech Intelligibility Advantages using an Acoustic Beamformer Display

A speech intelligibility test conforming to the Modified Rhyme Test of ANSI S3.2 "Method for Measuring the Intelligibility of Speech Over Communication Systems" was conducted using a prototype 12-channel acoustic beamformer system. The target speech material (signal) was identified against speech babble (noise), with calculated signal-noise ratios of 0, 5 and 10 dB. The signal was delivered at a fixed beam orientation of 135 deg (re 90 deg as the frontal direction of the array) and the noise at 135 deg (co-located) and 0 deg (separated). A significant improvement in intelligibility from 57% to 73% was found for spatial separation for the same signal-noise ratio (0 dB). Significant effects for improved intelligibility due to spatial separation were also found for higher signal-noise ratios (5 and 10 dB).

acoustic beamforming↗
NASA NTRS1993

Headphone localization of speech

Three-dimensional acoustic display systems have recently been developed that synthesize virtual sound sources over headphones based on filtering by head-related transfer functions (HRTFs), the direction-dependent spectral changes caused primarily by the pinnae. In this study, 11 inexperienced subjects judged the apparent spatial location of headphone-presented speech stimuli filtered with nonindividualized HRTFs. About half of the subjects 'pulled' their judgments toward either the median or the lateral-vertical planes, and estimates were almost always elevated. Individual differences were pronounced for the distance judgments; 15 to 46 percent of stimuli were heard inside the head, with the shortest estimates near the median plane. The results suggest that most listeners can obtain useful azimuth information from speech stimuli filtered by nonindividualized HRTFs. Measurements of localization error and reversal rates are comparable with a previous study that used broadband noise stimuli.

Begault, Durand R.↗
NASA NTRS1991

Headphone localization of speech stimuli

Recently, three dimensional acoustic display systems have been developed that synthesize virtual sound sources over headphones based on filtering by Head-Related Transfer Functions (HRTFs), the direction-dependent spectral changes caused primarily by the outer ears. Here, 11 inexperienced subjects judged the apparent spatial location of headphone-presented speech stimuli filtered with non-individualized HRTFs. About half of the subjects 'pulled' their judgements toward either the median or the lateral-vertical planes, and estimates were almost always elevated. Individual differences were pronounced for the distance judgements; 15 to 46 percent of stimuli were heard inside the head with the shortest estimates near the median plane. The results infer that most listeners can obtain useful azimuth information from speech stimuli filtered by nonindividualized RTFs. Measurements of localization error and reversal rates are comparable with a previous study that used broadband noise stimuli.

Begault, Durand R.↗
NASA NTRS1988

Space-Station-Interior Noise-Analysis Program

Intelligibility of speech evaluated for specified acoustical environments. Program makes systematic prediction of noise and vibration environment of craft defined by user and evaluates relative acceptability of predicted environment for effective communication by speech. Written in MicroSoft FORTRAN Version 3.3.

Stusnick, Eric↗
NASA NTRS1994

Virtual Acoustic Displays for Teleconferencing: Intelligibility Advantage for "Telephone Grade" Audio

Speech intelligibility was evaluated using a virtual acoustic ("3-D audio") display using the method specified by ANSI. Ten subjects were evaluated with stimuli either unfiltered or low-pass filtered at 4 kHz. Results show virtual acoustic techniques are advantageous for both full-bandwidth (44.1 kHz srate) and low (8 kHz srate) bandwidth "telephone-grade" teleconferencing systems.

Begault, Durand R.↗
DOE OSTI2022

The effect of simultaneous exposure on the attention selection and integration of segments and lexical tones by Urdu-Cantonese bilingual speakers

In the perceptual learning of lexical tones, an automatic and robust attention-to-phonology system enables native tonal listeners to adapt to acoustically non-optimal speech, such as phonetic conflicts in daily communications. Previous tone research reveals that non-native listeners who do not linguistically employ lexical tones in their mother tongue may find it challenging to attend to the tonal dimension or integrate it with the segmental features. However, it is unknown whether the attentional interference initially caused by a maternal attentional system would continue influencing the non-optimal tone perception for simultaneous bilingual teenagers. From an endpoint in the age of language acquisition, we investigate whether the tone-specific attention mechanism developed by the Urdu-Cantonese simultaneous bilinguals is automatic enough to assist them in adapting to a phonetically-conflicting environment. Three groups of teenagers engaged in a four-condition ABX task: Urdu-Cantonese simultaneous bilinguals, Cantonese native listeners, and Urdu-speaking, late learners of Cantonese. The results showed that although the simultaneous bilinguals could phonologically process Cantonese tones in a Cantonese-like way under a conflict-free listening condition, they still failed in adapting to the phonetic conflicts, especially the segment-induced ones. It thus demonstrated that the simultaneous exposure and years of regular education in Hong Kong local schools still could not automatically guarantee simultaneous bilingual processing of Cantonese tones. In interpreting the findings, it hypothesized that, except for simultaneous exposure, the development of a tone-specific attention mechanism is also likely to be L1-inhibitory, tone experience-driven, and language-specific for simultaneous bilinguals.

Ning, Jinghong↗
NASA NTRS2002

Improved Open-Microphone Speech Recognition

Many current and future NASA missions make extreme demands on mission personnel both in terms of work load and in performing under difficult environmental conditions. In situations where hands are impeded or needed for other tasks, eyes are busy attending to the environment, or tasks are sufficiently complex that ease of use of the interface becomes critical, spoken natural language dialog systems offer unique input and output modalities that can improve efficiency and safety. They also offer new capabilities that would not otherwise be available. For example, many NASA applications require astronauts to use computers in micro-gravity or while wearing space suits. Under these circumstances, command and control systems that allow users to issue commands or enter data in hands-and eyes-busy situations become critical. Speech recognition technology designed for current commercial applications limits the performance of the open-ended state-of-the-art dialog systems being developed at NASA. For example, today's recognition systems typically listen to user input only during short segments of the dialog, and user input outside of these short time windows is lost. Mistakes detecting the start and end times of user utterances can lead to mistakes in the recognition output, and the dialog system as a whole has no way to recover from this, or any other, recognition error. Systems also often require the user to signal when that user is going to speak, which is impractical in a hands-free environment, or only allow a system-initiated dialog requiring the user to speak immediately following a system prompt. In this project, SRI has developed software to enable speech recognition in a hands-free, open-microphone environment, eliminating the need for a push-to-talk button or other signaling mechanism. The software continuously captures a user's speech and makes it available to one or more recognizers. By constantly monitoring and storing the audio stream, it provides the spoken dialog manager extra flexibility to recognize the signal with no audio gaps between recognition requests, as well as to rerecognize portions of the signal, or to rerecognize speech with different grammars, acoustic models, recognizers, start times, and so on. SRI expects that this new open-mic functionality will enable NASA to develop better error-correction mechanisms for spoken dialog systems, and may also enable new interaction strategies.

Abrash, Victor↗
NASA NTRS2005

Small Vocabulary Recognition Using Surface Electromyography in an Acoustically Harsh Environment

This paper presents results of electromyographic-based (EMG-based) speech recognition on a small vocabulary of 15 English words. The work was motivated in part by a desire to mitigate the effects of high acoustic noise on speech intelligibility in communication systems used by first responders. Both an off-line and a real-time system were constructed. Data were collected from a single male subject wearing a fireghter's self-contained breathing apparatus. A single channel of EMG data was used, collected via surface sensors at a rate of 104 samples/s. The signal processing core consisted of an activity detector, a feature extractor, and a neural network classifier. In the off-line phase, 150 examples of each word were collected from the subject. Generalization testing, conducted using bootstrapping, produced an overall average correct classification rate on the 15 words of 74%, with a 95% confidence interval of [71%, 77%]. Once the classifier was trained, the subject used the real-time system to communicate and to control a robotic device. The real-time system was tested with the subject exposed to an ambient noise level of approximately 95 decibels.

Betts, Bradley J.↗
NASA NTRS2007

Applications for Subvocal Speech

A research and development effort now underway is directed toward the use of subvocal speech for communication in settings in which (1) acoustic noise could interfere excessively with ordinary vocal communication and/or (2) acoustic silence or secrecy of communication is required. By "subvocal speech" is meant sub-audible electromyographic (EMG) signals, associated with speech, that are acquired from the surface of the larynx and lingual areas of the throat. Topics addressed in this effort include recognition of the sub-vocal EMG signals that represent specific original words or phrases; transformation (including encoding and/or enciphering) of the signals into forms that are less vulnerable to distortion, degradation, and/or interception; and reconstruction of the original words or phrases at the receiving end of a communication link. Potential applications include ordinary verbal communications among hazardous- material-cleanup workers in protective suits, workers in noisy environments, divers, and firefighters, and secret communications among law-enforcement officers and military personnel in combat and other confrontational situations.

Jorgensen, Charles↗
NASA NTRS2009

Integrated Spacesuit Audio System Enhances Speech Quality and Reduces Noise

A new approach has been proposed for increasing astronaut comfort and speech capture. Currently, the special design of a spacesuit forms an extreme acoustic environment making it difficult to capture clear speech without compromising comfort. The proposed Integrated Spacesuit Audio (ISA) system is to incorporate the microphones into the helmet and use software to extract voice signals from background noise.

Huang, Yiteng Arden↗
NASA NTRS2004

Fluids and Combustion Facility Acoustic Emissions Controlled by Aggressive Low-Noise Design Process

The Fluids and Combustion Facility (FCF) is a dual-rack microgravity research facility that is being developed by Northrop Grumman Information Technology (NGIT) for the International Space Station (ISS) at the NASA Glenn Research Center. As an on-orbit test bed, FCF will host a succession of experiments in fluid and combustion physics. The Fluids Integrated Rack (FIR) and the Combustion Integrated Rack (CIR) must meet ISS acoustic emission requirements (ref. 1), which support speech communication and hearing-loss-prevention goals for ISS crew. To meet these requirements, the NGIT acoustics team implemented an aggressive low-noise design effort that incorporated frequent acoustic emission testing for all internal noise sources, larger-scale systems, and fully integrated racks (ref. 2). Glenn's Acoustical Testing Laboratory (ref. 3) provided acoustical testing services (see the following photograph) as well as specialized acoustical engineering support as part of the low-noise design process (ref. 4).

Cooper, Beth A.↗
NASA NTRS1972

Transmission line inversion and synthesis from the point of view of transient response

The transmission line inversion problem is applied to the speech communication process. The problem involves acquiring information necessary for synthesis of speech and for making models of the speech production mechanism. Formulation for the problem is derived from an analysis of the human vocal tract functions. It is known that speech sounds are produced by acoustic excitation of the tract by means of quasi-periodic pulses from the vocal cords during vowel sounds and turbulent air flow at various points along the tract during fricative sounds. By assuming plane wave propagation, differential equations are obtained relating the cross sectional area of the tract, the pressure, and the volume velocity. By replacing the pressure factor with a voltage factor and the volume velocity by current, the problem becomes a transmission line problem.

Sondhi, M. M.↗
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.↗