Nonlinear acoustics in the pant hoots of common chimpanzees (Pan troglodytes): vocalizing at the edge

Common chimpanzee (Pan troglodytes) "pant hoots" are multi-call events that build from quiet, consistently harmonic introductory sounds to loud, screamlike "climax" calls with acoustic irregularities known as "nonlinear phenomena" (NLP). Two possible functions of NLP in climax calls are to increase direct auditory impact on listeners and to signal physical condition. These possibilities were addressed by comparing climax calls from 12 wild chimpanzee males with "screams" and pant hoot "introduction" calls from the same individuals. Climax calls that included NLP were found to have higher fundamental frequencies (F0s) than introduction or climax calls that were purely harmonic. NLP onsets within climax calls were also specifically associated with local F0 maxima, suggesting vocalizers are vibrating their vocal folds at the upper limits of stability. Furthermore, climax calls showed far fewer NLP than did screams recorded from the same individuals, while showing equivalent or higher F0 values. Overall, the results are consistent with the hypothesis that the relative prevalence of NLP is a signal of physical condition, with callers "vocalizing at the edge" of regular, stable production while producing few NLP. The results are discussed in light of the initial hypotheses.     

Model-based detection of synthetic bat echolocation calls using an energy threshold detector for initialization

Detection of echolocation calls is fundamental to quantitative analysis of bat acoustic signals. Automated methods of detection reduce the subjectivity of hand labeling of calls and speed up the detection process in an accurate and repeatable manner. A model-based detector was initialized using a baseline energy threshold detector, removing the need for hand labels to train the model, and shown to be superior to the baseline detector using synthetic calls in two experiments: (1) an artificial environment and (2) a field playback setting. Synthetic calls using a piecewise exponential frequency modulation function from five hypothetical species were employed to control the signal-to-noise ratio (SNR) in each experiment and to provide an absolute ground truth to judge detector performance. The model-based detector outperformed the baseline detector by 2.5 dB SNR in the artificial environment and 1.5 dB SNR in the field playback setting. Atmospheric absorption was measured for the synthetic calls, and 1.5 dB increased the effective detection radius by between 1 and 7 m depending on species. The results demonstrate that hand labels are not necessary for training detection models and that model-based detectors significantly increase the range of detection for a recording system.     

Antimasking aspects of harp seal (Pagophilus groenlandicus) underwater vocalizations

Underwater sounds are very important in social communication of harp seals (Pagophilus groenlandicus) because they are the main means of long- and short-distance communication. Individual harp seals must try to avoid being masked and emit only those calls that will benefit them. Underwater vocalizations of harp seals were recorded during the breeding season. The physical characteristics associated with antimasking attributes of 16 call types were examined. Rising frequency or increasing amplitude within calls were not common. Most of the calls ended abruptly (range 145-966 dB/s), but call onset was more gradual. At high calling rates (95.1-135 calls/min) there were significantly more calls overlapping temporally than at medium (75.1-95 calls/min) or low (35-75 calls/min) calling rates, but even at the highest calling rates, 79.1% of the calls were not overlapped. When 2, 3, or 4 calls overlapped, there were significantly fewer frequency separations of less than 1/3 octave than would be expected by chance. This is important because sounds that are separated by less than 1/3 octave likely mask each other. When 2-4 calls are occurring simultaneously, only 4.5% to 14.2% are masked by virtue of being within 1/3 octave from their nearest neighbor. None of the overlappping calls was of the same type. This suggests that the seals are actively listening to each other's calls and are not randomly using the different call types. Harp seals use frequency and temporal separation in conjunction with a wide vocal repertoire to avoid masking each other.     

The effects of articulation on the acoustical structure of feline vocalizations

Feline isolation calls were analyzed, and a model was developed to relate the acoustical features of these calls to the physical processes used in their production. Fifty isolation calls were recorded from each of five cats for a total sample of 250 vocalizations. By combinations of Fourier transform, autocorrelation, and linear prediction methods, the fundamental frequency (glottal-pulse period) F0, the energy of F0, the frequency having maximum energy Fmax (not always F0), and the energy at this frequency were computed. Mean F0 ranged from 400-600 Hz for individual cats. For some cats F0 was consistent within calls, but for other cats sudden shifts in F0 occurred within calls. Here, Fmax was almost a harmonic of F0 and generally ranged from 1-2 kHz. For individual cats, the energy ratio E = (energy of Fmax/energy of F0) varied from 1 to 60 and the grand average E over the time course of the call varied from about 12 to 38. The mean rms call intensity was an inverted-U function of time. Measured jaw opening was strongly correlated with acoustical features of call. A Bessel-horn model with time-varying flare gave a good account of acoustical parameters such as Fmax. The presence of formantlike resonances in cat vocalizations and the important role of jaw movements (vocal gestures) in the production of these calls suggest that cats may provide a useful model for some aspects of human vocal behavior.     

Classification of communication signals of the little brown bat

Little brown bats, Myotis lucifugus, are known for their ability to echolocate and utilize their echolocation system to navigate, and locate and identify prey. Their echolocation signals have been characterized in detail but their communication signals are less well understood despite their widespread use during social interactions. The goal of this study was to develop an automatic classification algorithm for characterizing the communication signals of little brown bats. Sound recordings were made overnight on five individual male bats (housed separately from a large group of captive bats) for 7 nights, using a bat detector and a digital recorder. The spectral and temporal characteristics of recorded sounds were first analyzed and classified by visual observation of a call's temporal pattern and spectral composition. Sounds were later classified using an automatic classification scheme based on multivariate statistical parameters in MATLAB. Human- and machine-based analysis revealed five discrete classes of bat's communication signals: downward frequency-modulated calls, steep frequency-modulated calls, constant frequency calls, broadband noise bursts, and broadband click trains.     

Model-based automated detection of echolocation calls using the link detector

The link detector combines a model-based spectral peak tracker with an echo filter to detect echolocation calls of bats. By processing calls in the spectrogram domain, the links detector separates calls that overlap in time, including call harmonics and echoes. The links detector was validated by using an artificial recording environment, including synthetic calls, atmospheric absorption, and echoes, which provided control of signal-to-noise ratio and an absolute ground truth. Maximum hit rate (2% false positive rate) for the links detector was 87% compared to 1.5% for a spectral peak detector. The difference in performance was due to the ability of the links detector to filter out echoes. Detection range varied across species from 13 to more than 20 m due to call bandwidth and frequency range. Global features of calls detected by the links detector were compared to those of synthetic calls. The error in all estimates increased as the range increased, and estimates of minimum frequency and frequency of most energy were more accurate compared to maximum frequency. The links detector combines local and global features to automatically detect calls within the machine learning paradigm and detects overlapping calls and call harmonics in a unified framework.     

Automated detection and localization of bowhead whale sounds in the presence of seismic airgun surveys

An automated procedure has been developed for detecting and localizing frequency-modulated bowhead whale sounds in the presence of seismic airgun surveys. The procedure was applied to four years of data, collected from over 30 directional autonomous recording packages deployed over a 280 km span of continental shelf in the Alaskan Beaufort Sea. The procedure has six sequential stages that begin by extracting 25-element feature vectors from spectrograms of potential call candidates. Two cascaded neural networks then classify some feature vectors as bowhead calls, and the procedure then matches calls between recorders to triangulate locations. To train the networks, manual analysts flagged 219 471 bowhead call examples from 2008 and 2009. Manual analyses were also used to identify 1.17 million transient signals that were not whale calls. The network output thresholds were adjusted to reject 20% of whale calls in the training data. Validation runs using 2007 and 2010 data found that the procedure missed 30%-40% of manually detected calls. Furthermore, 20%-40% of the sounds flagged as calls are not present in the manual analyses; however, these extra detections incorporate legitimate whale calls overlooked by human analysts. Both manual and automated methods produce similar spatial and temporal call distributions.     

Sound production by North Atlantic right whales (Eubalaena glacialis) in surface active groups

The surface active group (SAG) is the most commonly observed surface social behavior of North Atlantic right whales. Recordings were made from 52 SAGs in the Bay of Fundy, Canada between July and September, from 1999 to 2002. The call types recorded from these groups were similar to those described previously for Southern right whales (Eubalaena australis), with six major call types being termed scream, gunshot, blow, upcall, warble, and downcall. The percentage of total calls of each call type depended on the group size and composition. The most common call type recorded was the scream call. The scream calls were produced by the focal female in a SAG. Production of other sound types can be attributed to whales other than the focal female, with gunshot and upcalls produced by males, and warble calls produced by female calves. The source levels for these sounds range from 137 to 162 dB rms re 1 ,tPa-m for tonal calls and 174 to 192 dB rms for broadband gunshot sounds.     

Vocal development in captive harbor seal pups, Phoca vitulina richardii: age, sex, and individual differences

The goal of this research was to determine when harbor seal pup vocalizations become sufficiently distinctive to allow individual recognition. A total of 4593 calls were analyzed from 15 captive pups. Nineteen were harsh, broadband, staccato calls used in an aggressive context. The rest were tonal "mother attraction calls," having an inverted "v"- or "u"-shaped spectrogram with harmonics and a fundamental frequency around 200-600 Hz. Calls were individually distinctive even in pups less than 2 weeks old, suggesting that mothers may be able to recognize pup vocalizations at this early age. Classification rates from discriminant function analysis were generally comparable to those of other phocids and less than in otariids, supporting the theory that recognition is more highly developed in otariids. Significant differences were found between male and female pup calls, and there were significant interactions between pup sex and age. The results of this study should be interpreted with caution until the findings are verified in wild harbor seal pups.     

Vocalization control in Mongolian gerbils (Meriones unguiculatus) during locomotion behavior

The vocalization behavior of Mongolian gerbils, a model animal of auditory physiology, was examined. A pair of gerbils was placed in a chamber, and their species-specific vocalizations and locomotive behaviors were recorded and analyzed. Two types of calls were predominantly produced: high-frequency upward frequency-modulated (HU-FM) calls and low-frequency multi-harmonic frequency-modulated (LM-FM) calls. Emission rates of HU-FM calls significantly decreased as the distance between the two gerbils increased, and playback of simulated HU-FM calls increased the emission rates. Acoustic analysis of HU-FM calls showed that the calls exhibited a stereotypic spectro-temporal structure including a fixed inter-onset interval (100-175 ms) and that individual differences in the frequency could convey the body size of the callers. The timing of HU-FM calls was highly synchronized with jump movements when an animal vocalized while jumping, suggesting the existence of tight locomotor-vocal coupling. Conversely, LM-FM calls were observed only when the gerbils tactilely contacted with each other while fighting over a food. These results suggest that Mongolian gerbils change the rates of call emissions and call types (e.g., LM-FM or HU-FM calls) in response to changes in visual and possibly tactile and auditory information. The functions of both calls are discussed in terms of their acoustic structures.     

Learned vocalizations in budgerigars (Melopsittacus undulatus): the relationship between contact calls and warble song

The budgerigar (Melopsittacus undulatus) has an extraordinarily complex, learned, vocal repertoire consisting of both the long rambling warble song of males and a number of short calls produced by both sexes. In warble, the most common elements (>30%) bear a strong resemblance to the highly frequency-modulated, learned contact calls that the birds produce as single utterances. However, aside from this apparent similarity, little else is known about the relationship between contact calls and warble call elements. Here, both types of calls were recorded from four male budgerigars. Signal analysis and psychophysical testing procedures showed that the acoustic features of these two vocalizations were acoustically different and perceived as distinctive vocalizations by birds. This suggests that warble call elements are not simple insertions of contact calls but are most likely different acoustic elements, created de novo, and used solely in warble. Results show that, like contact calls, warble call elements contain information about signaler identity. The fact that contact calls and warble call elements are acoustically and perceptually distinct suggests that they probably represent two phonological systems in the budgerigar vocal repertoire, both of which arise by production learning.     

Quantitative acoustic analysis of the vocal repertoire of the golden rocket frog (Anomaloglossus beebei)

This study describes the vocal repertoire of the Guyanan golden rocket frog, Anomaloglossus beebei, a bromeliad specialist with biparental care. Using multivariate analyses of nine call properties, as well as the occurrence of nonlinear phenomena, three signal types were distinguished-advertisement, courtship, and aggressive calls. Although all three call types were composed of a short series of rapidly repeated pulses, advertisement calls were produced at higher amplitudes and had longer pulse durations than both courtship calls and aggressive calls. Courtship calls exhibited lower dominant frequencies than both advertisement and aggressive calls, which had similar dominant frequencies. Aggressive calls had more pulses per call, had longer intervals between calls, and occasionally contained one or two introductory pulses preceding the pulsed call. Several acoustic properties predicted aspects of the signaler's body size and condition. Our study demonstrates the reliability of human observers to differentiate the multiple call types of A. beebei based on hearing calls and observing the social context in which they are produced under field conditions.     

Sources of acoustic variation: implications for production specificity and call categorization in chacma baboon (Papio ursinus) grunts

Elucidating the information content of vocal signals is fundamental to the understanding of animal communication. Acoustically distinct calls produced in specific contexts allow listeners to predict future events and choose adequate responses. However, the vocal repertoires of most terrestrial mammals consist of a limited number of call types that vary within and between categories. These "graded signaling systems" are thought to be rich in information, at the cost of increasing uncertainty regarding call categorization. In this study, patterns of acoustic variation in grunts of wild chacma baboons (Papio ursinus) were assessed in relation to different contexts, callers' arousal, the presence of listeners, and individual identity. Although overall production specificity was low, and sensitive to the number of contexts under consideration, grunts given in three contexts could be statistically distinguished from each other. Contextual differences remained when controlling for caller arousal, suggesting that these differences cannot be explained by variation in arousal. No audience effect was detected, but individual identity was found to have an influence on acoustic structure. Overall, these results support the view that, in comparison to other signaling systems associated with hazardous conditions, lower production specificity might evolve under relaxed circumstances where unambiguous signaling is less important.     

Nonoptimal propagation of advertisement calls of midwife toads in Iberian habitats

This study compares the efficiency of transmission of the advertisement calls of two species of midwife toads, Alytes cisternasii and A. obstetricans, in both native and non-native habitats in the Iberian Peninsula. Recorded calls of both species and pure tones were broadcast at ten sites native to either the relatively small A. cisternasii or the larger A. obstetricans. A large variation in the patterns of excess attenuation between localities was observed for calls measured at distances of 0.5 to 8 m from a loudspeaker. However, attenuation rates were higher for calls of both species in habitats of A. obstetricans relative to habitats of A. cisternasii. The calls of A. obstetricans experienced lower attenuation rates than those of A. cisternasii in both conspecific and heterospecific localities. Thus, although A. cisternasii occupies habitats more favorable for sound transmission, its advertisement call spectrum is not optimized for these habitats; the calls of A. obstetricans suffer less attenuation in A. cisternasii habitats. This result argues against the notion that spectral features of the calls are adapted to enhance transmission efficiency in natural habitats, and suggests that differences in call dominant frequency between the two species result from constraints imposed by selection on body size.     

Option pricing and perfect hedging on correlated stocks

We develop a theory for option pricing with perfect hedging in an inefficient market model where the underlying price variations are autocorrelated over a time τ0. This is accomplished by assuming that the underlying noise in the system is derived by an Ornstein-Uhlenbeck, rather than from a Wiener process. With a modified portfolio consisting in calls, secondary calls and bonds we achieve a riskless strategy which results in a closed and exact expression for the European call price which is always lower than Black-Scholes price. We obtain the same price and a modified delta hedging if we start from an effective one-dimensional market model. We compare these strategies and study the sensitivity of the call price to several parameters where the correlation effects are also observed.     

Responses of squirrel monkeys to their experimentally modified mobbing calls

Previous acoustic analyses suggested emotion-correlated changes in the acoustic structure of squirrel monkey (Saimiri sciureus) vocalizations. Specifically, calls given in aversive contexts were characterized by an upward shift in frequencies, often accompanied by an increase in amplitude. In order to test whether changes in frequencies or amplitude are indeed relevant for conspecific listeners, playback experiments were conducted in which either frequencies or amplitude of mobbing calls were modified. Latency and first orienting response were measured in playback experiments with six adult squirrel monkeys. After broadcasting yaps with increased frequencies or amplitude, squirrel monkeys showed a longer orienting response towards the speaker than after the corresponding control stimuli. Furthermore, after broadcasting yaps with decreased frequencies or amplitude, squirrel monkeys showed a shorter orienting response towards the speaker than after the corresponding manipulated calls with higher frequencies or amplitude. These results suggest that changes in frequencies or amplitude were perceived by squirrel monkeys, indicating that the relationship between call structure and the underlying affective state of the caller agreed with the listener's assessment of the calls. However, a simultaneous increase in frequencies and amplitude did not lead to an enhanced response, compared to each single parameter. Thus, from the receiver's perspective, both call parameters may mutually replace each other.     

Low frequency vocalizations attributed to sei whales (Balaenoptera borealis)

Low frequency (<100 Hz) downsweep vocalizations were repeatedly recorded from ocean gliders east of Cape Cod, MA in May 2005. To identify the species responsible for this call, arrays of acoustic recorders were deployed in this same area during 2006 and 2007. 70 h of collocated visual observations at the center of each array were used to compare the localized occurrence of this call to the occurrence of three baleen whale species: right, humpback, and sei whales. The low frequency call was significantly associated only with the occurrence of sei whales. On average, the call swept from 82 to 34 Hz over 1.4 s and was most often produced as a single call, although pairs and (more rarely) triplets were occasionally detected. Individual calls comprising the pairs were localized to within tens of meters of one another and were more similar to one another than to contemporaneous calls by other whales, suggesting that paired calls may be produced by the same animal. A synthetic kernel was developed to facilitate automatic detection of this call using spectrogram-correlation methods. The optimal kernel missed 14% of calls, and of all the calls that were automatically detected, 15% were false positives.