Does it sound better behind Miles Davis’ back? – What would it sound like face-to-face? Rushing through a holographic sound image of the trumpet
Franz Zotter – email@example.com
Matthias Frank – firstname.lastname@example.org
University of Music and Performing Arts Graz
Institute of Electronic Music and Acoustics (IEM)
Inffeldgasse 10/3, 8010 Graz, Austria
Popular version of paper 2pAAa4, “Challenges of musical instrument reproduction including directivity”
Presented Tuesday afternoon, November 3, 2015, 2:25 PM, Grand Ballroom 3
170th ASA Meeting, Jacksonville
In many of his concerts, Miles Davis used to play his trumpet facing away from the audience. Would it have made a difference had he faced the audience?
Unplugged acoustical instruments can feature a tremendously different timbre for different orientations. Musicians experience such effects while playing their instrument in different environments. Those lacking such experience can only learn about the so-called directivity of musical instruments from publications showing diagrams of measured timbral changes. Comprehensive publications from the nineteen sixties deliver remarkably detailed descriptions. And yet, it requires training to imagine how the timbral changes sound like by just looking at these diagrams.
In the new millennium, researchers built surrounding spheres of microphones that allow to record a holographic sound image of any musical instrument (Figure 1). This was done to get a more natural representation of instruments in virtual acoustic environments for games or computer-aided acoustic design. Alternatively, the holographic sound image can be played back in real environments using a compact spherical loudspeaker array (Figure 2).
Such a recording allows, for instance, to convey a tangible experience of how strongly the timbre and loudness of a trumpet changes with orientation. (Audio example 1) is an excerpt from a corresponding holographic sound image using 64 surrounding microphones. With each repetition of the excerpt, the recording position gradually moves from behind the instrumentalist to the face-to-face orientation.
While what was shown above was done under the exclusion of acoustical influences of the room, the new kind of holographic sound imagery is a key technology used to reproduce a fully convincing experience of a musical instrument within arbitrary rooms it is played in.
A surrounding sphere of 64 microphone was built at IEM (Fabian Hohl, 2009) to record holographic sound images of musical instruments. The photo (Fabian Hohl, 2009) shows Silvio Rether playing the trumpet.
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The icosahedron as a housing of 20 loudspeakers (a compact spherial loudspeaker array) was built 2006 at IEM. It is a device to play back holographic sound images of musical instruments. Currently, it is used as a new tool in computer music to project sound into rooms utilizing wall reflections from different directions.
The photo (Franz Zotter, 2010) shows the icosahedral loudspeaker during concert rehearsals.
In the example, one can clearly hear the orientation-related timbral changes of the trumpet. The short excerpt is played in 7 repetitions, each time recorded at another position, moving from behind the trumpet player to the front. The piece “Gaelforce” by Peter Graham is performed by Silvio Rether, and the recording was done by Fabian Hohl at IEM using the sphere shown in Figure 1.
Popular version of paper 4aEA2, “Monitoring hardening of concrete using ultrasonic guided waves” Presented Thursday morning, Nov. 5, 2015, 8:50 AM, ORLANDO room,
170th ASA Meeting, Jacksonville, FL
Concrete is the most commonly used construction material in the world. The performance of concrete structures is largely determined by properties of fresh concrete at early ages. Concrete gains strength through a chemical reaction between water and cement (hydration), which gradually change a fluid fresh concrete mix to a rigid and hard solid. The process is called setting and hardening. It is important to measure the setting times, because you may not have enough time to mix and place concrete if the setting time is too early, while too late setting will cause delay in strength gain. The setting and hardening process is affected by many parameters, including water and cement ratio, temperature, and chemical admixtures. The standard method to test setting time is to measure penetration resistance of fresh concrete samples in laboratory, which may not represent the real condition in field.
Ultrasonic waves have been proposed to monitor the setting and hardening process of concrete by measuring wave velocity change. When concrete becomes hard, the stiffness increases, and the ultrasonic velocity also increases. The authors found there is a clear relationship between the shear wave velocity and the traditional penetration resistance. However, most ultrasonic tests measure a small volume of concrete sample in laboratory, and they are not suitable for field application. In this paper, the authors proposed an ultrasonic guided wave test method. Steel reinforcements (rebars) are used in most concrete structures. When ultrasonic guided waves propagate within rebar, they leak energy to surrounding concrete, and the energy leakage rate is proportion to the stiffness of concrete. Ultrasonic waves can be introduced into rebars from one end and the echo signal will be received at the same end using the same ultrasonic sensor. This test method has a simple test setup, and is able to monitor the concrete hardening process continuously.
Figure 2 shows guided wave echo signals measured on a 19mm diameter rebar embedded in concrete. It is clear that the signal amplitude decreases with the age of concrete (2 ~ 6 hours). The attenuation can be plotted vs. age for different cement/concrete mixes. Figure 3 shows the attenuation curves for 3 cement paste mixes. It is known that a cement mix with larger water cement ratio (w/c) will have slower strength gain, which agrees with the ultrasonic guided wave test, where the w/c=0.5 mix has lower attenuation rate. When there is a void around the rebar, energy leakage will be less than the case without a void, which is also confirmed by the test result in Figure 3.
Summary: This study presents experimental results using ultrasonic guided waves to monitor concrete setting and hardening process. It shows the guided wave leakage attenuation is proportional to the stiffness change of fresh concrete. Therefore the leakage rate can be used to monitor the concrete strength gain at early ages. This study may have broader applications in other disciplines to measure mechanical property of material using guided wave.
Figure. 1 Principle of ultrasonic guided wave test.
Figure. 2 Ultrasonic echo signals measured in an embedded rebar for concrete age of 2~6 hours.
Figure. 3 Guided wave attenuation rate in a rebar embedded in different cement pastes.
Popular version of paper 2pAAa10, “High-resolution measurements of speech directivity”
Presented Tuesday afternoon, November 3, 2015, 4:40 PM, Grand Ballroom 3
170th ASA Meeting, Jacksonville
In general, most sources of sound do not radiate equally in all directions. The human voice is no exception to this rule. How strongly sound is radiated in a given direction at a specific frequency, or pitch, is called directivity. While many [references] have studied the directivity of speaking and singing voices, some important details are missing. The research reported in this presentation measured directivity of live speech at higher angular and frequency resolutions than have been previously measured, in an effort to capture the missing details.
The approach uses a semicircular array of 37 microphones spaced with five-degree polar-angle increments, see Figure 1. A subject sits on a computer-controlled rotating chair with his or her mouth aligned at the axis of rotation and circular center of the microphone array. He or she repeats a series of phonetically-balanced sentences at each of 72 five-degree azimuthal-angle increments. This results in 2522 measurement points on a sphere around the subject.
[Figure 1. A subject and the measurement array]
The measurements are based on audio recordings of the subject who tries to repeat the sentences with exactly the same timing and inflection at each rotation. To account for the inevitable differences in each repetition, a transfer function and the coherence between a reference microphone near the subject and a measurement microphone on the semicircular array is computed. The coherence is used to examine how good each measurement is. The transfer function for each measurement point makes up the directivity. To visualize the results, each measurement is plotted on a sphere, where the color and the radius of the sphere indicate how strongly sound is radiated in that direction for a given frequency. Animations of these spherical plots show how the directivity differs for each frequency.
[Figure 2. Balloon plot for male speech directivity at 500 and 1000 Hz.]
[Figure 3. Balloon plot for female speech directivity at 500 and 1000 Hz.]
Some unique results are visible in the animations. Most importantly, as frequency increases, one can see that most of the sound is radiated in the forward direction. This is one reason for why it’s hard to hear someone talking in the front of a car when you’re sitting in the back, unless they turn around to talk to you. One can also see in the animations that as frequency increases, and most of the sound radiates forwards, there is poor coherence in the back area. This doesn’t necessarily indicate a poor measurement, just poor signal-to-noise ratio, since there is little sound energy in that direction. It’s also interesting to see that the polar angle of the strongest radiation also changes with frequency. At some frequencies the sound is radiated strongly downward and to the sides, but at other frequencies the stound is radiated strongly upwards and forwards. Male and female directivities are similar in shape, but at different frequencies, since the fundamental frequency of males and females is so different.
A more complete understanding of speech directivity has great benefits to several industries. For example, hearing aid companies can use speech directivity patterns to know where to aim microphones in the hearing aids to pick up the best sound for the hearing aid wearer having a conversation. Microphone placement in cell phones can be adjusted to get clearer signal from those talking into the cell phone. The theater and audio industries can use directivity patterns to assist in positioning actors on stage, or placing microphones near the speakers to record the most spectrally rich speech. The scientific community can develop more complete models for human speech based on these measurements. Further study on this subject will allow researchers to improve the measurement method and analysis techniques to more fully understand the results, and generalize them to all speech containing similar phonemes to those in these measurements.
Popular version of paper 4aAB2, “Seemingly simple songs: Black-capped chickadee song revisited”
Presented Thursday morning, November 5, 8:55 AM, City Terrace Room
170th ASA Meeting, Jacksonville, Fl
Vocal communication is a mode of communication important to many animal species, including humans. Over the past 60 years, songbird vocal communication has been widely-studied, largely because the invention of the sound spectrograph allows researchers to visually represent vocalizations and make precise acoustic measurements. Black-capped chickadees (Poecile atricapillus; Figure 1) are one example of a songbird whose song has been well-studied. Black-capped chickadees produce a short (less than 2 seconds), whistled fee-bee song. Compared to the songs produced by many songbird species, which often contain numerous note types without a fixed order, black-capped chickadee song is relatively simple, containing two notes produced in the same order during each song rendition. Although the songs appear to be acoustically simple, they contain a rich variety of information about the singer including: dominance rank, geographic location, and individual identity [1,2,3].
Interestingly, while songbird song has been widely-examined, most of the focus (at least for North Temperate Zone species) has been on male-produced song, largely because it was thought that only males actually produced song. However, more recently, there has been mounting evidence that in many songbird species, both males and females produce song [4,5]. In the study of black-capped chickadees, the focus has also been on male-produced song. However, recently, we reported that female black-capped chickadees also produce fee-bee song. One possible reason that female song has not been extensively reported is that to human vision, male and female chickadees are visually identical, so females that are singing may be mistakenly identified as male. However, by identifying a bird’s sex (via DNA analysis) and recording both males and females, our work  has shown that female black-capped chickadees do produce fee-bee song. Additionally, these songs are overall acoustically similar to male song (songs of both sexes contain two whistled notes; see Figure 2), making vocal discrimination by humans difficult.
Our next objective was to determine if any acoustic features varied between male and female songs. Using bioacoustic techniques, we were able to demonstrate that there are acoustic differences in male and female song, with females producing songs that contain a greater frequency decrease in the first note compared to male songs (Figure 2). These results demonstrate that there are sufficient acoustic differences to allow birds to identify the sex of a signing individual even in the absence of visual cues. Because birds may live in densely wooded environments, in which visual, but not auditory, cues are often obscured, being able to identify the sex of a bird (and whether the singer is a potential mate or territory rival) would be an important ability.
Following our bioacoustic analysis, an important next step was to determine whether birds are able to distinguish between male and female songs. In order to examine this, we used a behavioral paradigm that is common in animal learning studies: operant conditioning. By using this task, we were able to demonstrate that birds can distinguish between male and female songs; however, the particular acoustic features birds use in order to discriminate between the sexes may depend on the sex of the bird that is listening to the song. Specifically, we found evidence that male subjects responded based on information in the song’s first note, while female subjects responded based on information in the song’s second note . One possible reason for this difference in responding is that in the wild, males need to quickly respond to a rival male that is a territory intruder, while females may assess the entire song to gather as much information about the singing individual (for example, information regarding a potential mate’s quality). While the exact function of female song is unknown, our studies clearly indicate that female black-capped chickadees produce songs and the birds themselves can perceive differences between male and female songs.
Figure 1. An image of a black-capped chickadee.
Figure 2. Spectrogram (x-axis: time; y-axis: frequency in kHz) on a male song (top) and female song (bottom).
Sound file 1. An example of a male fee-bee song.
Sound file 2. An example of a female fee-bee song.
Hoeschele, M., Moscicki, M.K., Otter, K.A., van Oort, H., Fort, K.T., Farrell, T.M., Lee, H., Robson, S.W.J., & Sturdy, C.B. (2010). Dominance signalled in an acoustic ornament. Animal Behaviour, 79, 657–664.
Hahn, A.H., Guillette, L.M., Hoeschele, M., Mennill, D.J., Otter, K.A., Grava, T., Ratcliffe, L.M., & Sturdy, C.B. (2013). Dominance and geographic information contained within black-capped chickadee (Poecile atricapillus) song. Behaviour, 150, 1601-1622.
Christie, P.J., Mennill, D.J., & Ratcliffe, L.M. (2004). Chickadee song structure is individually distinctive over long broadcast distances. Behaviour 141, 101–124.
Langmore, N.E. (1998). Functions of duet and solo songs of female birds. Trends in Ecology and Evolution, 13, 136–140.
Riebel, K. (2003). The “mute” sex revisited: vocal production and perception learning in female songbirds. Advances in the Study of Behavior, 33, 49–86
Hahn, A.H., Krysler, A., & Sturdy, C.B. (2013). Female song in black-capped chickadees (Poecile atricapillus): Acoustic song features that contain individual identity information and sex differences. Behavioural Processes, 98, 98-105.
Hahn, A.H., Hoang, J., McMillan, N., Campbell, K., Congdon, J., & Sturdy, C.B. (2015). Biological salience influences performance and acoustic mechanisms for the discrimination of male and female songs. Animal Behaviour, 104, 213-228.
Mice ultrasonic detection and localization in laboratory environment
Yegor Sinelnikov – email@example.com Alexander Sutin, Hady Salloum, Nikolay Sedunov, Alexander Sedunov
Stevens Institute of Technology
Hoboken, NJ 07030
Tom Zimmerman, Laurie Levine
DLAR Stony Brook University
Stony Brook, NY 11790
Department of Homeland Security
Science and Technology Directorate
Popular version of poster 1pABb1, “Mice ultrasonic detection and localization in laboratory environment” Presented Tuesday afternoon, November 3, 2015, 3:30 PM, Grand Ballroom 3
170th ASA Meeting, Jacksonville
A house mouse, mus musculus, historically shares the human environment without much permission. It lives in our homes, enjoys our husbandry, and passes through walls and administrative borders unnoticed and unaware of our wary attention. Over the thousands of years of coexistence, mice excelled in a carrot and stick approach. Likewise, an ordinary wild mouse brings both danger and cure to humans todays. A danger is in the form of rodent-borne diseases, amongst them plague epidemics, well remembered in European medieval history, continue to pose a threat to human health. A cure is in the form of lending themselves as research subjects for new therapeutic agents, an airily misapprehension of genomic similarities, small size, and short life span. Moreover, physiological similarity in inner ear construction, brain auditory responses and unexpected richness in vocal signaling attested to the tremendous interest to mice bioacoustics and emotion perception.
The goal of this work is to start addressing possible threats reportedly carried by invasive species crossing US borders unnoticed in multiple cargo containers. This study focuses on demonstrating the feasibility of acoustic detection of potential rodent intrusions.
Animals communicate with smell, touch, movement, visual signaling and sound. Mice came well versed in sensorial abilities to face the challenge of sharing habitat with humans. Mice gave up color vision, developed exceptional stereoscopic smell, and learned to be deceptively quiet in human auditory range, discretely shifting their social acoustic interaction to higher frequencies. They predominantly use ultrasonic frequencies above the human hearing range as a part of their day-to-day non aggressive social interaction. Intricate ultrasonic mice songs composed of multiple syllable sounds often constituting complex phrases separated by periods of silence are well known to researchers.
In this study, mice sounds were recorded in a laboratory environment at an animal facility at Stony Brook University Hospital. The mice were allowed to move freely, a major condition for their vocalization in ultrasonic range. Confined to cages, mice did not produce ultrasonic signals. Four different microphones with flat ultrasonic frequency response were positioned in various arrangements and distances from the subjects. The distances varied from a few centimeters to several meters. An exemplary setup is shown in Figure 1. Three microphones, sensitive in the frequency range between 20 kHz and 100 kHz, were connected to preamplifiers via digital converters to a computer equipped with dedicated sound recording software. The fourth calibrated microphone was used for measurements of absolute sound level produced by a mouse. The spectrograms were monitored by an operator in real time to detect the onset of mice communications and simplify line data processing.
Figure 1. Setup of experiment showing the three microphones (a) on a table with unrestrained mouse (b), recording equipment preamplifiers and digitizers (c) and computer (d).
Listen to a single motif of mice ultrasonic vocalization and observe mouse movement here:
This sound fragment was down converted (slowed down) fifteen times to be audible. In reality, mice social songs are well above the human audible range and are very fast. The spectrograms of mice vocalization at distances of 1 m and 5 m are shown in Figure 2. Mice vocalization was detectable at 5 m and retained recognizable vocalization pattern. Farther distances were not tested due to the limitation of the room size.
The real time detection of mice vocalization required detection of the fast, noise insensitive and automated algorithm. An innovative approach was required. Recognizing that no animal communication comes close to become a language, the richness and diversity of mice ultrasonic vocalization prompted us to apply speech processing measures for their real time detection. A number of generic speech processing measures such temporal signal to noise ratio, cepstral distance, and likelihood ratio were tested for the detection of mice vocalization events in the presence of background noise. These measures were calculated from acoustical measurements and compared with conventional techniques, such as bandpass filtering, spectral power, or continuous monitoring of signal frames for the presence of expected tones.
Figure 2. Sonograms of short ultrasonic vocalization syllables produced by mice at 1 m (left) and 5 m (right) distances from microphones. The color scale is in the decibels.
Although speech processing measures were invented to assess human speech intelligibility, we found them applicable for the acoustic mice detection within few meters. Leaving aside the question about mice vocalization intelligibly, we concluded that selected speech processing measures enabled us to detect events of mice vocalization better than other generic signal processing techniques.
As a secondary goal of this study, upon successful acoustic detection, the mice vocalization needed to be processed to determine animal location. It was of main interest for border patrol applications, where both acoustic detection and spatial localization are critical, and because mice movement has a behavioral specificity. To prove the localization feasibility, detected vocalization events from each microphone pair were processed to determine the time difference of arrival (TDOA). The analysis was limited to nearby locations by relatively short cabling system. Because the animals were moving freely on the surface of a laboratory table, roughly coplanar with microphones, the TDOA values were converted to the animal location using simple triangulation scheme. The process is illustrated schematically in Figure 3 for two selected microphones. Note that despite low signal to noise ratio for the microphone 2, the vocalization events were successfully detected. The cross correlograms, calculated in spectral domain with empirical normalization to suppress the effect of uncorrelated noise, yielded reliable TDOA. A simple check for the zero sum of TDOA was used as a consistency control. Calculated TDOA were converted into spatial locations, which were assessed for correctness, experimental and computational uncertainties and compared with available video recordings. Despite relatively high level of technogenic noise, the TDOA calculated locations agreed well with video recordings. The TDOA localization uncertainty was estimated on the order of the mouse size, roughly corresponding to several wavelengths at 50 kHz. A larger number of microphones is expected to improve detectability and enable more precise three dimensional localization.
Hence, mice ultrasonic socialization sounds are detectable by the application of speech processing techniques, their TDOA are identifiable by cross correlation and provide decent spatial localization of animals in agreement with video observations.
Figure 3. The localization process. First, the detected vocalization events from two microphones (left) are paired and their cross correlogram is calculated (middle). The maxima, marked by asterisks, define a set of identified TDOA. The process is repeated for every pair of microphones. Second, the triangulation is performed (right). The colored hyperbolas illustrate possible locations of animal on a laboratory table based on calculated TDOA. Hyperbolas intersection provides the location of animal. The numbered squares mark the location of microphones.
1The constructed recording system is particularly important for the detection of mice in containers at US ports of entry, where low frequency noises are high. This pilot study confirms the feasibility of using Stevens Institute’s ultrasonic recording system for simultaneous detection of mice vocalization and movement.
This work was funded by the U.S. Department of Homeland Security’s Science and Technology Directorate. The views and conclusions contained in this paper are those of the authors and should not necessarily be interpreted as representing the official policies, either expressed or implied of the U.S. Department of Homeland Security.