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Results for “SPEECH DISCRIMINATION”

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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17 records
All sourcesNASA NTRSDOE OSTI
NASA NTRS1988

Binaural speech discrimination under noise in hearing-impaired listeners

This paper presents the results of an assessment of speech discrimination by hearing-impaired listeners (sensori-neural, conductive, and mixed groups) under binaural free-field listening in the presence of background noise. Subjects with pure-tone thresholds greater than 20 dB in 0.5, 1.0 and 2.0 kHz were presented with a version of the W-22 list of phonetically balanced words under three conditions: (1) 'quiet', with the chamber noise below 28 dB and speech at 60 dB; (2) at a constant S/N ratio of +10 dB, and with a background white noise at 70 dB; and (3) same as condition (2), but with the background noise at 80 dB. The mean speech discrimination scores decreased significantly with noise in all groups. However, the decrease in binaural speech discrimination scores with an increase in hearing impairment was less for material presented under the noise conditions than for the material presented in quiet.

Kumar, K. V.↗
NASA NTRS1980

Role of the middle ear muscle apparatus in mechanisms of speech signal discrimination

A method of impedance reflexometry was used to examine 101 students with hearing impairment in order to clarify the interrelation between speech discrimination and the state of the middle ear muscles. Ability to discriminate speech signals depends to some extent on the functional state of intraaural muscles. Speech discrimination was greatly impaired in the absence of stapedial muscle acoustic reflex, in the presence of low thresholds of stimulation and in very small values of reflex amplitude increase. Discrimination was not impeded in positive AR, high values of relative thresholds and normal increase of reflex amplitude in response to speech signals with augmenting intensity.

Moroz, B. S.↗
NASA NTRS2006

Open Microphone Speech Understanding: Correct Discrimination Of In Domain Speech

An ideal spoken dialogue system listens continually and determines which utterances were spoken to it, understands them and responds appropriately while ignoring the rest This paper outlines a simple method for achieving this goal which involves trading a slightly higher false rejection rate of in domain utterances for a higher correct rejection rate of Out of Domain (OOD) utterances. The system recognizes semantic entities specified by a unification grammar which is specialized by Explanation Based Learning (EBL). so that it only uses rules which are seen in the training data. The resulting grammar has probabilities assigned to each construct so that overgeneralizations are not a problem. The resulting system only recognizes utterances which reduce to a valid logical form which has meaning for the system and rejects the rest. A class N-gram grammar has been trained on the same training data. This system gives good recognition performance and offers good Out of Domain discrimination when combined with the semantic analysis. The resulting systems were tested on a Space Station Robot Dialogue Speech Database and a subset of the OGI conversational speech database. Both systems run in real time on a PC laptop and the present performance allows continuous listening with an acceptably low false acceptance rate. This type of open microphone system has been used in the Clarissa procedure reading and navigation spoken dialogue system which is being tested on the International Space Station.

Hieronymus, James↗
NASA NTRS1967

Speech communication

Computer analysis of speech, vowel perception by children, and articulatory activity during production of intervocalic fricative consonants

COMPUTER METHOD↗
NASA NTRS1967

Speech communication

Linguistic and speech communication concepts on mechanism of glottal vibration for vowels and consonants, and homomorphic speech processing

COMMUNICATION SYSTEM↗
NASA NTRS1990

Evaluation of speech recognizers for use in advanced combat helicopter crew station research and development

The U.S. Army Crew Station Research and Development Facility uses vintage 1984 speech recognizers. An evaluation was performed of newer off-the-shelf speech recognition devices to determine whether newer technology performance and capabilities are substantially better than that of the Army's current speech recognizers. The Phonetic Discrimination (PD-100) Test was used to compare recognizer performance in two ambient noise conditions: quiet office and helicopter noise. Test tokens were spoken by males and females and in isolated-word and connected-work mode. Better overall recognition accuracy was obtained from the newer recognizers. Recognizer capabilities needed to support the development of human factors design requirements for speech command systems in advanced combat helicopters are listed.

Simpson, Carol A.↗
NASA NTRS1991

Communication variations related to leader personality

While communication and captain personality type have been separately shown to relate to overall crew performance, this study attempts to establish a link between communication and personality among 12 crews whose captains represent three pre-selected personality profiles (IE+, I-, Ec-). Results from analyzing transcribed speech from one leg of a full-mission simulation study, so far indicate several discriminating patterns involving ratios of total initiating speech (captain to crew members); in particular commands, questions and observations.

Kanki, Barbara G.↗
DOE OSTI2022

Speaker-targeted Synthetic Speech Detection

Text-to-speech technologies are evolving quickly towards realistic-sounding human-like voices. As this technology improves, so does the opportunity for malpractice in speaker identification (SID) via spoofing, the process of impersonating a voice biometric via synthesis. More data typically equates to a more realistic voice model, which poses an issue for well-known subjects, such as politicians and celebrities, who have vast amounts of multimedia available online. Detection of synthetic speech has relied on signal processing techniques that focus on the generation of new acoustic features and train deep learning models to detect when an audio file has been manipulated through the characterization of unnatural changes or artifacts. However, these techniques do not use any information from the speaker they are evaluating. This paper proposes to incorporate information from the speaker-of-interest (SoI) into the models to avoid specific spoofing attacks for certain vulnerable people. The wealth of data for well-known people can also be used to train a speaker-specific spoofing detector with a higher level of accuracy than a speaker-independent model. The paper proposes a new xResNet-PLDA system and compares it to three different baseline systems: a state-of-the-art speaker identification system, an xResNet system trained to discriminate between bona fide and fake speech, and a speaker identification system in which the PLDA and calibration models were trained with bona fide and fake speech. We evaluated the systems in two different scenarios — a cross-validation scenario and a hold-out scenario — with three different databases. We show how the proposed system outperforms dramatically the baseline systems in each scenario and for each database. Finally, we show how using a small amount of the SoI’s speech to adapt global calibration parameters improves the performance of the system, especially in unseen conditions.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
NASA NTRS2007

Noise-Canceling Helmet Audio System

A prototype helmet audio system has been developed to improve voice communication for the wearer in a noisy environment. The system was originally intended to be used in a space suit, wherein noise generated by airflow of the spacesuit life-support system can make it difficult for remote listeners to understand the astronaut s speech and can interfere with the astronaut s attempt to issue vocal commands to a voice-controlled robot. The system could be adapted to terrestrial use in helmets of protective suits that are typically worn in noisy settings: examples include biohazard, fire, rescue, and diving suits. The system (see figure) includes an array of microphones and small loudspeakers mounted at fixed positions in a helmet, amplifiers and signal-routing circuitry, and a commercial digital signal processor (DSP). Notwithstanding the fixed positions of the microphones and loudspeakers, the system can accommodate itself to any normal motion of the wearer s head within the helmet. The system operates in conjunction with a radio transceiver. An audio signal arriving via the transceiver intended to be heard by the wearer is adjusted in volume and otherwise conditioned and sent to the loudspeakers. The wearer s speech is collected by the microphones, the outputs of which are logically combined (phased) so as to form a microphone- array directional sensitivity pattern that discriminates in favor of sounds coming from vicinity of the wearer s mouth and against sounds coming from elsewhere. In the DSP, digitized samples of the microphone outputs are processed to filter out airflow noise and to eliminate feedback from the loudspeakers to the microphones. The resulting conditioned version of the wearer s speech signal is sent to the transceiver.

Seibert, Marc A.↗
DOE OSTI2016

Neural speech recognition: continuous phoneme decoding using spatiotemporal representations of human cortical activity

The superior temporal gyrus (STG) and neighboring brain regions play a key role in human language processing. Previous studies have attempted to reconstruct speech information from brain activity in the STG, but few of them incorporate the probabilistic framework and engineering methodology used in modern speech recognition systems. Here, in this work, we describe the initial efforts toward the design of a neural speech recognition (NSR) system that performs continuous phoneme recognition on English stimuli with arbitrary vocabulary sizes using the high gamma band power of local field potentials in the STG and neighboring cortical areas obtained via electrocorticography. The system implements a Viterbi decoder that incorporates phoneme likelihood estimates from a linear discriminant analysis model and transition probabilities from an n-gram phonemic language model. Grid searches were used in an attempt to determine optimal parameterizations of the feature vectors and Viterbi decoder. The performance of the system was significantly improved by using spatiotemporal representations of the neural activity (as opposed to purely spatial representations) and by including language modeling and Viterbi decoding in the NSR system. These results emphasize the importance of modeling the temporal dynamics of neural responses when analyzing their variations with respect to varying stimuli and demonstrate that speech recognition techniques can be successfully leveraged when decoding speech from neural signals. Guided by the results detailed in this work, further development of the NSR system could have applications in the fields of automatic speech recognition and neural prosthetics.

59 BASIC BIOLOGICAL SCIENCES↗
NASA NTRSDate not supplied

Speech-Enhanced and Context Dependent Alerts: Future Implications for Spacecraft Design Abstract

In the future, NASA missions will involve many different space vehicles, habitats, and surface assets working together to provide safe and productive living and working environments for crew. Because these systems will be provided by multiple commercial companies working with NASA, it will be very different from missions of the past, bringing new challenges. One of the challenges is related to whether NASA should move beyond simple tone annunciation alerting systems, to more advanced systems that include speech. The other is related to determining the level of consistency required of safety-critical alert systems across spacecraft. Two studies were completed to address these important issues. The first study investigated the advantages and disadvantages of a tone+speech alert relative to the traditional tone-only alert. Results indicate that speech-enhanced alerts initially take longer to silence (the default action to which NASA personnel are trained), due to the need to listen to the entire message, but ultimately provided for faster understanding of the alert situation. Speech-enhanced alerts were also preferred by a large majority of crew-like study participants. An unexpected finding from this first study was that participants took longer to respond to tone-only alerts when they were mixed with speech- enhanced alerts. Participants waited to hear the speech message even for alerts they were trained to know did not contain speech components. This performance error is believed to be due to negative transfer of training. A second study focused on task and alert performance using a common set of tones across two contexts (“vehicles”) versus performance with a different set of tones for each context (“vehicle”). Participants were able to manage two different alert sets successfully; results indicate that discriminability of the two alert sets played a major role in their success. Implications for the design of spacecraft alerts are discussed and future areas of research are identified.

alerts↗
NASA NTRS2023

Speech-Enhanced and Context Dependent Alerts: Future Implications for Spacecraft Design

In the future, NASA missions will involve many different space vehicles, habitats, and surface assets working together to provide safe, productive environments for crew. Because these systems will be provided by multiple commercial companies working with NASA, it will be very different from missions of the past, bringing new challenges. One of the challenges is related to whether NASA should move beyond simple tone annunciation alerting systems, to more advanced systems that include speech. The other is related to determining the level of consistency required of safety-critical alert systems across spacecraft. Two studies were completed to address these important issues. The first study investigated the advantages and disadvantages of a tone+speech alert relative to the traditional tone-only alert. Results indicate that speech-enhanced alerts initially take longer to silence (the default action to which NASA personnel are trained), due to the need to listen to the entire message, but ultimately provided for faster understanding of the alert situation. Speech-enhanced alerts were also preferred by a large majority of crew-like study participants. An unexpected finding was that participants took longer to respond to tone-only alerts that were heard in the same session as speech-enhanced alerts. Participants waited to hear a speech message even for alerts they were trained to know did not contain speech components. This performance error is believed to be due to negative transfer of training. A second study focused on task and alert performance using a common set of tones across two contexts (e.g., vehicles, habitats, suits) versus performance with a different set of tones for each context. Participants were able to manage two different alert sets successfully; results indicate that discriminability of the two alert sets played a major role in their success. Implications for the design of spacecraft alerts are discussed, and future areas of research are identified.

alerts↗