The what and where of synchronous sound perception

Sound localization and identification are challenging in acoustically rich environments. The relation between these two processes is still poorly understood. As natural sound-sources rarely occur exactly simultaneously, we wondered whether the auditory system could identify ('what') and localize ('where') two spatially separated sounds with synchronous onsets. While listeners typically report hearing a single source at an average location, one study found that both sounds may be accurately localized if listeners are explicitly being told two sources exist. We here tested whether simultaneous source identification (one vs. two) and localization is possible, by letting listeners choose to make either one or two head-orienting saccades to the perceived location(s). Results show that listeners could identify two sounds only when presented on different sides of the head, and that identification accuracy increased with their spatial separation. Notably, listeners were unable to accurately localize either sound, irrespective of whether one or two sounds were identified. Instead, the first (or only) response always landed near the average location, while second responses were unrelated to the targets. We conclude that localization of synchronous sounds in the absence of prior information is impossible. We discuss that the putative cortical 'what' pathway may not transmit relevant information to the 'where' pathway. We examine how a broadband interaural correlation cue could help to correctly identify the presence of two sounds without being able to localize them. We propose that the persistent averaging behavior reveals that the 'where' system intrinsically assumes that synchronous sounds originate from a single source.

Spontaneous emergence of music detectors in a deep neural network trained for natural sound recognition

Music exists in almost every society, has universal acoustic features, and is processed by distinct neural circuits in humans even with no experience of musical training. These characteristics suggest an innateness of the sense of music in our brain, but it is unclear how this innateness emerges and what functions it has. Here, using an artificial deep neural network that models the auditory information processing of the brain, we show that units tuned to music can spontaneously emerge by learning natural sound detection, even without learning music. By simulating the responses of network units to 35,487 natural sounds in 527 categories, we found that various subclasses of music are strongly clustered in the embedding space, and that this clustering arises from the music-selective response of the network units. The music-selective units encoded the temporal structure of music in multiple timescales, following the population-level response characteristics observed in the brain. The process of generalization was critical for the emergence of music-selectivity, as such properties were absent when the label of the training data was randomized to prevent generalization. We confirmed that music-selectivity can work as a functional basis for the generalization of natural sound, thereby elucidating its origin. These findings suggest that our sense of music can be innate, universally shaped by evolutionary adaptation to process natural sound.

Distinct timescales for the neuronal encoding of vocal signals in a high-order auditory area

The ability of the auditory system to selectively recognize natural sound categories while maintaining a certain degree of tolerance towards variations within these categories, which may have functional roles, is thought to be crucial for vocal communication. To date, it is still largely unknown how the balance between tolerance and sensitivity to variations in acoustic signals is coded at a neuronal level. Here, we investigate whether neurons in a high-order auditory area in zebra finches, a songbird species, are sensitive to natural variations in vocal signals by recording their responses to repeated exposures to identical and variant sound sequences. We used the songs of male birds which tend to be highly repetitive with only subtle variations between renditions. When playing these songs to both anesthetized and awake birds, we found that variations between songs did not affect the neuron firing rate but the temporal reliability of responses. This suggests that auditory processing operates on a range of distinct timescales, namely a short one to detect variations in vocal signals, and longer ones that allow the birds to tolerate variations in vocal signal structure and to encode the global context.

Natural sound characteristics explain perceptual categorization

As we interact with our surroundings, we encounter the same or similar objects from different perspectives and are compelled to generalize. For example, we recognize dog barks as a distinct class of sound, despite the variety of individual barks. While we have some understanding of how generalization is done along a single stimulus dimension, such as frequency or color, natural stimuli are identifiable by a combination of dimensions. To understand perception, measuring the interaction across stimulus dimensions is essential. For example, when identifying a sound, does our brain focus on a specific dimension or a combination, such as its frequency and duration? Furthermore, does the relative relevance of each dimension reflect its contribution to the natural sensory environment? Using a 2-dimension discrimination task for mice we tested untrained generalization across several pairs of auditory dimensions. We uncovered a perceptual hierarchy over the tested dimensions that was dominated by the sound’s spectral composition. A model tuned to the predictability inherent in natural sounds best explained the behavioral results, suggesting that the perceptual hierarchy parallels the predictive content of natural sounds.

KAJIAN SOUNDSCAPE DI RUANG PUBLIK TERBUKA TENGAH KOTA PADA MASA PANDEMI COVID-19 (STUDI KASUS: TAMAN CATTLEYA, TOMANG, JAKARTA BARAT)

Urban public spaces are public spaces that are visited by many urban residents with all the activities they can do. In the urban public space, various kinds of voices or sounds fill this space. Voices can be heard from any room or place in the city. The natural environment, humans, and mechanical equipment produce sound landscapes or soundscapes in the city space air. In urban public spaces, activities carried out by humans can produce artificial sound, while natural activities produce natural sound. The purpose of this study is to describe and explore the sound landscape in urban public space. This research was conduct on holidays, by observing various types of sounds and voices, the distribution of sources, time, and strength of sounds and voices to achieve the research objectives. Found that after the observation, in the open public space of Cattleya Tomang Park, West Jakarta, the results of mechanical sound sources came from the roar of motorized vehicles and the sound of construction work was more dominant than natural sounds that came from humans, trees, and animals. Research on soundscapes in urban public spaces is expected to be a basis for consideration in designing urban public spaces so that public spaces can be enjoyed more by city residents who use them. Abstrak: Ruang publik kota merupakan ruang publik yang banyak dikunjungi oleh warga kota dengan segala kegiatan yang bisa dilakukan. Di dalam ruang publik kota, berbagai ragam suara atau bunyi mengisi ruang ini. Bentang suara dapat didengar dari berbagai ragam ruang atau tempat di kota. Alam lingkungan, manusia, maupun peralatan mekanik memproduksi bentang suara atau soundscape di udara ruang kota. Di ruang publik kota, kegiatan yang dilakukan oleh oleh manusia dapat menghasilkan bunyi, sementara kegiatan alami menghasilkan suara. Tujuan penelitian ini adalah untuk menggambarkan dan mengeksplorasi bentang suara yang berada di ruang publik kota. Penelitian ini dilakukan pada hari libur, dengan mengobservasi berbagai macam jenis bunyi dan suara, sebaran sumber, waktu, dan kekuatan bunyi dan suara untuk mencapai tujuan penelitian. Didapati setelah pengamatan, pada ruang publik terbuka Taman Cattleya Tomang, Jakarta Barat, hasil sumber bunyi mekanik berasal dari deru mesin kendaraan bermotor dan bunyi pekerjaan konstruksi pembangunan gedung lebih dominan dibandingkan dengan suara alami yang datang dari manusia, pepohonan, maupun hewan. Penelitian soundscape di ruang publik kota ini diharapkan dapat menjadi dasar pertimbangan dalam perancangan ruang publik kota agar ruang publik lebih dapat dinikmati oleh warga kota yang memanfaatkannya.

Audio Classification for Noise Filtering Using Convolutional Neural Network Approach

In each part of daily routine, sound assumes a significant part. From discrete security features to basic reconnaissance, a sound is a vivacious component to create automated frameworks for these fields. Scarcely any frameworks are now on the lookout, yet their effectiveness is a concerned point for their execution, real-time conditions. The learning capacities of Deep learning designs can be utilized to create sound characterization frameworks increase the impact of sound classification. Our main aim in this paper is to implement deep learning networks for filtering the nose and arrangement of these sound created by the natural phenomenon’s according to the spectrograms that are created accordingly. The spectrograms of these natural sounds are utilized for the preparation of the Convolutional neural network (CNN) and Tensor Deep Stacking Network (TDSN). The utilized datasets for analysis and creation of the networks are ESC-10 and ESC-50. These frameworks produced from these datasets were efficient in accomplishment of filtering the audio and recognizing the audio of the natural sound. The precision obtained from the developed system is 80% for CNN and 70% for TDSN. Form the implemented framework, it is presumed that proposed approach for sound filtering and recognition through the utility spectrogram of their subsequent sounds can be productively used to create efficient frameworks for audio classification and recognition based on neural networks.

Distinct timescales for the neuronal encoding of vocal signals in a high-order auditory area

The ability of the auditory system to selectively recognize natural sound categories with a tolerance to variations within categories is thought to be crucial for vocal communication. Subtle variations, however, may have functional roles. To date, how the coding of the balance between tolerance and sensitivity to variations in acoustic signals is performed at the neuronal level requires further studies. We investigated whether neurons of a high-order auditory area in a songbird species, the zebra finch, are sensitive to natural variations in vocal signals by recording responses to repeated exposure to similar and variant sound sequences. We took advantage of the intensive repetition of the male songs which subtly vary from rendition to rendition. In both anesthetized and awake birds, responses based on firing rate during sequence presentation did not show any clear sensitivity to these variations, unlike the temporal reliability of responses based on a 10 milliseconds resolution that depended on whether variant or similar sequences were broadcasted and the context of presentation. Results therefore suggest that auditory processing operates on distinct timescales, a short one to detect variations in individual's vocal signals, longer ones that allow tolerance in vocal signal structure and the encoding of the global context.

A synthesis of health benefits of natural sounds and their distribution in national parks

Parks are important places to listen to natural sounds and avoid human-related noise, an increasingly rare combination. We first explore whether and to what degree natural sounds influence health outcomes using a systematic literature review and meta-analysis. We identified 36 publications examining the health benefits of natural sound. Meta-analyses of 18 of these publications revealed aggregate evidence for decreased stress and annoyance (g = −0.60, 95% CI = −0.97, −0.23) and improved health and positive affective outcomes (g = 1.63, 95% CI = 0.09, 3.16). Examples of beneficial outcomes include decreased pain, lower stress, improved mood, and enhanced cognitive performance. Given this evidence, and to facilitate incorporating public health in US national park soundscape management, we then examined the distribution of natural sounds in relation to anthropogenic sound at 221 sites across 68 parks. National park soundscapes with little anthropogenic sound and abundant natural sounds occurred at 11.3% of the sites. Parks with high visitation and urban park sites had more anthropogenic sound, yet natural sounds associated with health benefits also were frequent. These included animal sounds (audible for a mean of 59.3% of the time, SD: 23.8) and sounds from wind and water (mean: 19.2%, SD: 14.8). Urban and other parks that are extensively visited offer important opportunities to experience natural sounds and are significant targets for soundscape conservation to bolster health for visitors. Our results assert that natural sounds provide important ecosystem services, and parks can bolster public health by highlighting and conserving natural soundscapes.

The typologically rare approximant inventory of Kajkwakhrattxi: A series of natural sound changes

Kajkwakhrattxi, a Northern Jê language spoken by fewer than 30 elders in Mato Grosso, Brazil, exhibits a typologically rare sound inventory, especially with respect to its series of approximants: /w, w̃, ʍ, ɽ, ɽ̃, j/, realized as a total of 17 different surface allophones: [w, w̃͡w, w̃, ʍ, ɥ, ɥ̃͡ɥ, ɥ̃, ɥ̊, ɾ, ɾ̃, ɽ, ɽ̃, ɻ, ɻ̃, ɻ̊, j, j̃]. We propose a novel reconstruction of Proto-Northern-Jê that accounts for this unusually dense inventory of approximants, namely as the result of a series of natural sound changes involving processes of lenition and assimilation. Our analysis makes use of novel fieldwork data on three underdocumented and endangered languages of the family: Kajkwakhrattxi, Panãra, and Kayapô. As a result, our reconstruction is based on a more phonetically detailed and internally coherent data set than was available to previous comparative work on Jê languages. Our results provide evidence for the possible breadth of diversity in the phonological systems of natural languages, both synchronically and diachronically, and advances our knowledge of the sound changes that occurred from Proto-Northern-Jê to its daughter languages.