Fundamental frequency (F0) estimation for quasiharmonic signals is an important task in music signal processing. Many previously developed techniques have suffered from unsatisfactory performance due to ambiguous spectra, noise perturbations, wide frequency range, vibrato, and other common artifacts encountered in musical signals. In this paper a new two-way mismatch (TWM) procedure for estimating F0 is described which may lead to improved results in this area. This computer-based method uses the quasiharmonic assumption to guide a search for F0 based on the short-time spectra of an input signal. The estimated F0 is chosen to minimize discrepancies between measured partial frequencies and harmonic frequencies generated by trial values of F0. For each trial F0, mismatches between the harmonics generated and the measured partial frequencies are averaged over a fixed subset of the available partials. A weighting scheme is used to reduce the susceptibility of the procedure to the presence of noise or absence of certain partials in the spectral data. Graphs of F0 estimate versus time for several representative recorded solo musical instrument and voice passages are presented. Some special strategies for extending the TWM procedure for F0 estimations of two simultaneous voices in duet recordings are also discussed.

Automatic off-line classification and recognition of bird vocalizations has been a subject of interest to ornithologists and pattern detection researchers for many years. Several new applications, including bird vocalization classification for aircraft bird strike avoidance, will require real time classification in the presence of noise and other disturbances. The vocalizations of many common bird species can be represented using a sum-of-sinusoids model. An experiment using computer software to perform peak tracking of spectral analysis data demonstrates the usefulness of the sum-of-sinusoids model for rapid automatic recognition of isolated bird syllables. The technique derives a set of spectral features by time-variant analysis of the recorded bird vocalizations, then performs a calculation of the degree to which the derived parameters match a set of stored templates that were determined from a set of reference bird vocalizations. The results of this relatively simple technique are favorable for both clean and noisy recordings.

Audio recordings of gunshots can provide information about the gun location with respect to the microphone(s), the speed and trajectory of the projectile, and in some cases the type of firearm and ammunition. Recordings obtained under carefully controlled conditions can be well-modeled by geometrical acoustics. Special acoustic processing systems for real time gunshot detection and localization are used by the military and law enforcement agencies for sniper detection. Forensic analysis of audio recordings is also used to provide evidence in criminal and civil cases. This paper reviews the distinctive features and limitations of acoustic gunshot analysis using DSP techniques.

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The spatiotemporal variability of ground-level ozone (GLO) in the rural Annapolis Valley, Nova Scotia was investigated between August 29, 2006, and September 28, 2007, using Ogawa nitrite-impregnated passive diffusion samplers (PS). A total of 353 PS measurements were made at 17 ambient and 1 indoor locations over 18 sampling periods ranging from 2 to 4 weeks. The calculated PS detection limit was 0.8 +/- 0.02 parts per billion by volume (ppbv), for a 14-day sampling period. Duplicate samplers were routinely deployed at three sites and these showed excellent agreement (R2 values of 0.88 [n = 11], 0.95 [n = 17], and 0.96 [n = 17]), giving an overall PS imprecision value of 5.4%. Comparisons between PS and automated continuous ozone analyzers at three sites also demonstrated excellent agreement with R2 values of 0.82, 0.95, and 0.95, and gradients not significantly different from unity. The minimum, maximum, and mean (+/- 1 sigma) ambient annual GLO concentrations observed were 7.7, 72.1, and 34.3 +/- 10.1 ppbv, respectively. The three highest sampling sites had significantly greater (P = 0.032) GLO concentrations than three Valley floor sites, and there was a strong correlation between concentration and elevation (R2 = 0.82). Multivariate models were used to parameterize the observed GLO concentrations in terms of prevailing meteorology at an elevated site found at Kejimkujik National Park and also at a site on the Valley floor. Validation of the multivariate models using 30 months of historical meteorological data at these sites yielded R2 values of 0.70 (elevated site) and 0.61 (Valley floor). The mean indoor ozone concentration was 5.4 +/- 3.3 ppbv and related to ambient GLO concentration by the equation: indoor = 0.34 x ambient - 5.07. This study has demonstrated the suitability of PS for long-term studies of GLO over a wide geographic area and the effect of topographical and meteorological influences on GLO in this region.

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