Sound Events Localization and Detection Using Bio-Inspired Gammatone Filters and Temporal Convolutional Neural Networks

Rosero, Karen; Grijalva, Felipe; Masiero, Bruno

doi:10.1109/taslp.2023.3284525

Cited by 10 publications

(1 citation statement)

References 27 publications

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“…The comparative investigation showed that the GTFs provided the highest speech detection accuracy compared to the Gaussian and Mel filters. A GTFbased sound event detection and localization (SEDL) system has been presented in [23]. The authors demonstrated that GTFs could boost the performance of state-of-the-art SEDL algorithms.…”

Section: Introductionmentioning

confidence: 99%

Investigating the Performance of Gammatone Filters and Their Applicability to Design Cochlear Implant Processing System

Islam,

Tarique

2024

Designs

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Commercially available cochlear implants are designed to aid profoundly deaf people in understanding speech and environmental sounds. A typical cochlear implant uses a bank of bandpass filters to decompose an audio signal into a set of dynamic signals. These filters’ critical center frequencies imitate the human cochlea’s vibration patterns caused by audio signals. Gammatone filters (GTFs), with two unique characteristics: (a) an appropriate “pseudo resonant” frequency transfer function, mimicking the human cochlea, and (b) realizing efficient hardware implementation, could demonstrate them as unique candidates for cochlear implant design. Although GTFs have recently attracted considerable attention from researchers, a comprehensive exposition of GTFs is still absent in the literature. This paper starts by enumerating the impulse response of GTFs. Then, the magnitude spectrum, , and bandwidth, more specifically, the equivalent rectangular bandwidth (ERB) of GTFs, are derived. The simulation results suggested that optimally chosen filter parameters, e.g., critical center frequencies,; temporal decay parameter, ; and order of the filter, , can minimize the interference of the filter bank frequencies and very likely model the filter bandwidth (ERB), independent of . Finally, these optimized filters are applied to delineate a filter bank for a cochlear implant design based on the Clarion processor model.

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Section: Introductionmentioning

confidence: 99%

Investigating the Performance of Gammatone Filters and Their Applicability to Design Cochlear Implant Processing System

Islam,

Tarique

2024

Designs

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Dynamics of interaction between IH and IKLT currents to mediate double resonances of medial superior olive neurons related to sound localization

Wang,

Gu,

Zhang

2023

Cogn Neurodyn

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Dynamic-Structured Reservoir Spiking Neural Network in Sound Localization

Roozbehi,

Narayanan,

Mohaghegh

et al. 2024

IEEE Access

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Sound source localization is a critical problem in various fields, including communication, security, and entertainment. Binaural cues are a natural technique used by mammalian ears for efficient sound source localization. Spiking neural networks (SNNs) have emerged as a promising tool for implementing binaural sound source localization approaches. However, optimizing the topology and size of SNNs is crucial to reduce computational costs while maintaining accuracy. This paper proposes a realtime structure of a reservoir SNN (rSNN) called Adaptive-Resonance-Theory-based rSNN (ART-rSNN) for localizing sound sources in the time domain by integrating an energy-based localization method. The dataset used in this work is recorded by two different omnidirectional microphones from a real environment. The dataset includes various sound events such as speech, music, and environmental sounds. The proposed ART-rSNN architecture can dynamically adjust the location of its neurons to amplify estimated energy near the sound source, resulting in higher localization accuracy. Our proposed method outperforms several conventional and state of the art algorithms in terms of accuracy and is able to detect the front and back direction of azimuth angle. This work demonstrates the potential of dynamic neuron arrangements in SNNs for improving sound source localization in practical applications

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Sound Events Localization and Detection Using Bio-Inspired Gammatone Filters and Temporal Convolutional Neural Networks

Cited by 10 publications

References 27 publications

Investigating the Performance of Gammatone Filters and Their Applicability to Design Cochlear Implant Processing System

Investigating the Performance of Gammatone Filters and Their Applicability to Design Cochlear Implant Processing System

Dynamics of interaction between IH and IKLT currents to mediate double resonances of medial superior olive neurons related to sound localization

Dynamic-Structured Reservoir Spiking Neural Network in Sound Localization

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