Spectro-Temporal Processing in a Two-Stream Computational Model of Auditory Cortex

Zulfiqar, Isma; Moerel, Michelle; Formisano, Elia

doi:10.3389/fncom.2019.00095

Cited by 21 publications

(18 citation statements)

References 82 publications

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“…As the input spectrogram is strided temporally by α, the intermediate feature maps have a lower temporal resolution. Moreover, the Slow stream has temporal convolutions only in res 4 1. Architecture details for Fig.…”

Section: Network Architecturementioning

confidence: 99%

“…There is strong evidence in neuroscience for the existence of two streams in the human auditory system, the ventral stream for identifying sound-emitting objects and the dorsal streams for locating these objects. Studies [3,4] suggest the ventral stream accordingly exhibits high spectral resolution for object identification, while the dorsal stream has a high temporal resolution and operates at a higher sampling rate.…”

Section: Introductionmentioning

confidence: 99%

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Slow-Fast Auditory Streams for Audio Recognition

Kazakos

Nagrani

Zisserman

et al. 2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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We propose a two-stream convolutional network for audio recognition, that operates on time-frequency spectrogram inputs. Following similar success in visual recognition, we learn Slow-Fast auditory streams with separable convolutions and multi-level lateral connections. The Slow pathway has high channel capacity while the Fast pathway operates at a fine-grained temporal resolution. We showcase the importance of our two-stream proposal on two diverse datasets: VGG-Sound and EPIC-KITCHENS-100, and achieve stateof-the-art results on both.

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Section: Network Architecturementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Slow-Fast Auditory Streams for Audio Recognition

Kazakos

Nagrani

Zisserman

et al. 2021

ICASSP 2021 - 2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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show abstract

“…Such a model, based on an integro-differential equation, has been successfully applied to describe the evolution of neural activations. In particular, it allowed theoretically predicting complex perceptual phenomena in V1, such as the emergence of hallucinatory patterns [12,17], and has been used in various computational models of the auditory cortex [26,37,46]. Recently, these equations have been coupled with the neurogeometric model of V1 to great benefit.…”

Section: A Rotated Sound Image Corresponds To a Completely Different mentioning

confidence: 99%

A bio-inspired geometric model for sound reconstruction

et al. 2021

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The reconstruction mechanisms built by the human auditory system during sound reconstruction are still a matter of debate. The purpose of this study is to propose a mathematical model of sound reconstruction based on the functional architecture of the auditory cortex (A1). The model is inspired by the geometrical modelling of vision, which has undergone a great development in the last ten years. There are, however, fundamental dissimilarities, due to the different role played by time and the different group of symmetries. The algorithm transforms the degraded sound in an ‘image’ in the time–frequency domain via a short-time Fourier transform. Such an image is then lifted to the Heisenberg group and is reconstructed via a Wilson–Cowan integro-differential equation. Preliminary numerical experiments are provided, showing the good reconstruction properties of the algorithm on synthetic sounds concentrated around two frequencies.

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“…The caudal or dorsal stream originates in areas located caudally to the primary core and projects via the parietal cortex to dorsal frontal regions (Scott et al, 2017). These two processing streams show distinct neuronal properties (Jasmin et al, 2019;Zulfiqar et al, 2020). Compared to primary and surrounding auditory areas, neurons in the rostral field exhibit longer response latencies and narrower frequency tuning (Recanzone et al, 2000;Tian et al, 2001;Bendor and Wang, 2008;Camalier et al, 2012).…”

Section: Information Processing Pathwaysmentioning

confidence: 99%

“…Spectro-temporal Processing in a Two-Stream Computational Model of Auditory Cortex Zulfiqar, I., Moerel, M., and Formisano, E. (2020)…”

Section: Chaptermentioning

confidence: 99%

From Neurons to Behavior

Zulfiqar

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Spectro-Temporal Processing in a Two-Stream Computational Model of Auditory Cortex

Cited by 21 publications

References 82 publications

Slow-Fast Auditory Streams for Audio Recognition

Slow-Fast Auditory Streams for Audio Recognition

A bio-inspired geometric model for sound reconstruction

From Neurons to Behavior

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