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Enhancing Mental Readiness in Military Personnel
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In: DTIC (2006)
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| 2 |
Towards a Formal Ontology for Military Coalitions Operations
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In: DTIC (2005)
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| 3 |
Comment ameliorer la selection et le traitement des messages verbaux? (How to Improve the Selection and Processing of Verbal Messages)
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In: DTIC (2005)
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| 4 |
Evaluation of Speech Synthesis Systems using the Speech Reception Threshold Methodology
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In: DTIC (2005)
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| 6 |
Objective Measurement of the Speech Transmission Quality of Vocoders by Means of the Speech Transmission Index
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In: DTIC (2005)
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| 7 |
Analysis of Free-Form Battlefield Reports with Shallow Parsing Techniques
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In: DTIC AND NTIS (2004)
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| 8 |
The Case for Using Semantic Nets as a Convergence Format for Symbolic Information Fusion
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In: DTIC AND NTIS (2004)
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| 9 |
Electronic Information Management and Intellectual Property Rights
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In: DTIC AND NTIS (2004)
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| 10 |
Ontological Approach to Military Knowledge Modeling and Management
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In: DTIC AND NTIS (2004)
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| 11 |
Some Psycho-Physiological and Cognitive Implications of Hypobaric Exposure during Selection of Slovak Astronaut Candidates
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In: DTIC AND NTIS (2001)
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| 12 |
Towards Multilingual Interoperability in Automatic Speech Recognition
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In: DTIC (2000)
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| 13 |
Clustering of Context Dependent Speech Units for Multilingual Speech Recognition
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In: DTIC (2000)
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| 14 |
Speech Intelligibility of Native and Non-Native Speech
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In: DTIC (2000)
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| 15 |
Auditory Features Underlying Cross-Language Human Capabilities in Stop Consonant Discrimination
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In: DTIC (2000)
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Abstract:
For some phonemic distinctions human listeners exhibit a marked cross-language capability, in that they are capable of highly correct classification in relation to sounds (like CVs or VCVs) uttered by speakers of another language. This is particularly true regarding distinctions that are perceived in a more categorical fashion, like that of 3-way PLACE discrimination in stop consonants. It is plausible that the reason for this is a mostly common (across languages) auditory basis for human communication of this discrimination. Also, human communication of this discrimination is notably impervious to non-drastic variations in the frequency- transfer curve, which suggests that the relevant auditory features must have some inherent insensitivity to these variations. Models for two specialized auditory cells (onset cells with wide receptive fields, which can detect weak onsets synchronized across frequency, and sequence cells which detect frequency-ascending sequences composed of two onsets) were refined for the discrimination of DENTAL vs LABIAL stop consonants and applied to large spelling databases in Portuguese, German, and U.S. English. Similar discriminatory capability was observed both for German and U.S. English. Integration with a 3rd auditory feature resulted in error scores of approximately 2% when exactly the same model is applied to either German or U.S. English sounds. ; Presented at the Information Systems Technology Panel (IST) Tutorial and Workshop held in Leusden, The Netherlands, 13-14 September 1999. This article is from ADA387529 Multi-Lingual Interoperability in Speech Technology (l'Interoperabilite multilinguistique dans la technologie de la parole)
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Keyword:
*AUDITORY SIGNALS; *HEARING; *SPEECH RECOGNITION; *VOICE COMMUNICATIONS; Anatomy and Physiology; AUDITORY PERCEPTION; COMMUNICATION AND RADIO SYSTEMS; COMPONENT REPORTS; DISCRIMINATION; ENGLISH LANGUAGE; ERRORS; FOREIGN REPORTS; GRAPHS; HUMANS; LANGUAGE; Linguistics; NATO FURNISHED; PHONETICS; PORTUGAL; SOUND; SPEECH ANALYSIS; SYMPOSIA; Voice Communications
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URL: http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADP010385
http://www.dtic.mil/docs/citations/ADP010385
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| 16 |
Vowel System Modeling: A Complement to Phonetic Modeling in Language Identification
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In: DTIC (2000)
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| 17 |
Comparing Three Methods to Create Multilingual Phone Models for Vocabulary Independent Speech Recognition Tasks
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In: DTIC (2000)
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| 18 |
Speech Recognition of Non-Native Speech Using Native and Non-Native Acoustic Models
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In: DTIC (2000)
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| 19 |
Multilingual Vocabularies in Automatic Speech Recognition
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In: DTIC (2000)
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| 20 |
Speech Recognition by Goats, Wolves, Sheep and Non-Natives
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In: DTIC (2000)
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