Two experiments were conducted to evaluate the effects of increasing spectral bandwidth from 3 to 10 kHz on individual speaker recognition in noisy conditions (+5, 0, and −5 dB signal-to-noise ratio). Experiment 1 utilized h(Vowel)d (hVd) signals, while experiment 2 utilized sentences from the Rainbow Passage. Both experiments showed significant improvements in individual speaker identification in the 10 kHz bandwidth condition (6% for hVds; 10% for sentences). These results coincide with the extant machine recognition literature demonstrating significant amounts of individual speaker information present in the speech signal above approximately 3–4 kHz. Cues from the high-frequency region for speaker identity warrant further study.
This paper is focused on analyzing effects of several significant parameters on the performance of an immunity-inspired methodology for autonomous navigation of unmanned air vehicles when measurements from global navigation satellite systems (GNSS) or similar current sources, including external information of opportunity, are not available. An artificial immune system (AIS) provides corrections to a dead reckoning algorithm for adequate estimates of vehicle position and velocity. Parameter effects are assessed and analyzed through simulation in terms of trajectory tracking errors during autonomous flight.
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