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Lexical Link Analysis Application: Improving Web Service to Acquisition Visibility Portal
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In: DTIC (2013)
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| 62 |
Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
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In: DTIC (2013)
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| 63 |
Contextual Awareness for Robust Robot Autonomy
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In: DTIC (2013)
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| 64 |
Faust: Flexible Acquistion and Understanding System for Text
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In: DTIC (2013)
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| 65 |
Extending Semantic and Episodic Memory to Support Robust Decision Making
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In: DTIC (2013)
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| 66 |
Interacting with Multi-Robot Systems Using BML
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In: DTIC (2013)
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| 68 |
Cybernetic configurations: characteristics of interactivity in the digital arts.
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| 72 |
Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program Awareness
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In: DTIC (2012)
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| 73 |
Adding a Capability to Extract Sentiment from Text Using HanDles
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In: DTIC (2012)
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| 74 |
Speech Synthesis Using Perceptually Motivated Features
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In: DTIC (2012)
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| 75 |
Machine Recognition vs Human Recognition of Voices
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In: DTIC (2012)
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Abstract:
While automated speaker recognition by machines can be quite good as demonstrated in NIST Speaker Recognition Evaluations, performance can still suffer when environmental conditions, emotions, or recording quality change. This research examines how robust humans are compared with machines at speaker recognition in changing environments. Several data conditions, including short sentences, frequency selective noise, and time-reversed speech were used to test the robustness of human listeners versus machine algorithms. Statistical significance tests were completed on the results and, for under conditions, human speaker recognition was more robust. The strength of the human listeners was especially evident for the challenging case of noise in the 2000-3000 Hz frequency range. Additional analysis was performed to identify factors that may impact a listener's ability to identify a person's identity. For example, the amount of voiced (or unvoiced) speech was examined to see if there was a correlation with how easily a speaker's voice was recognized. Unfortunately, the amount of voiced (or unvoiced) speech did not correlate strongly with how easily a speaker's voice was recognized. Other factors such as fundamental pitch, formant locations, pitch shimmer, pitch jitter, and other modulation measures also are being examined. The original goal of this effort was to discover which frequency bands are most important for the familiar speaker recognition task. This research was a cursory look at what frequency information is important for speaker identification. More listening experiments with better randomization of stimuli and phonetic consideration are required. ; See also ADA561051. Presented at the International Conference on Acoustics, Speech and Signal Processing (37th) (ICASSP 2012) held in Kyoto, Japan, on March 25-30, 2012. Published in the Proceedings of the 37th International Conference on Acoustics, Speech and Signal Processing, p4245-4248, 2012. U.S. Government or Federal Purpose Rights License. The original document contains color images.
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Keyword:
*AUDIO FREQUENCY; *FAMILIAR SPEAKERS; *FREQUENCY BANDS; *HUMAN PERFORMANCE; *LEARNING MACHINES; *MACHINE PERFORMANCE; *PERFORMANCE(ENGINEERING); *PERFORMANCE(HUMAN); *SIGNAL TO NOISE RATIO; *SPEAKER IDENTIFICATION; *SPEAKER RECOGNITION; *SPEECH RECOGNITION; Acoustics; ALGORITHMS; AUDITORY SIGNALS; BACKGROUND NOISE; CO-WORKER IDENTIFICATION; CUES(STIMULI); Cybernetics; HEARING DEFICIT GROUP; HUMAN LISTENERS; IDENTIFICATION; NORMAL HEARING GROUP; Psychology; SIGNAL PROCESSING; SPEAKER CUES; SPEAKER FAMILIARITY; SPEECH SIGNAL DEGRADATION; SPEECH SIGNALS; SPEECH-SHAPED ADDITIVE NOISE; STATISTICAL ANALYSIS; SYMPOSIA; TRAINING; Voice Communications
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URL: http://www.dtic.mil/docs/citations/ADA568903
http://oai.dtic.mil/oai/oai?&verb=getRecord&metadataPrefix=html&identifier=ADA568903
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| 76 |
Simon Plays Simon Says: The Timing of Turn-Taking in an imitation Game
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In: DTIC (2012)
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| 77 |
For and from Cyberspace: Conceptualizing Cyber Intelligence, Surveillance, and Reconnaissance
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In: DTIC (2012)
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| 78 |
Uncovering and Managing the Impact of Methodological Choices for the Computational Construction of Socio-Technical Networks from Texts
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In: DTIC (2012)
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| 79 |
Making the Most of MASINT and Advanced Geospatial Intelligence
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In: DTIC (2012)
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| 80 |
Compressed Domain Automatic Level Control Based on ITU-T G.722.2
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In: DTIC (2012)
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