☆ 4.7 Article

Characterization of Moving Sound Sources Direction-of-Arrival Estimation Using Different Deep Learning Architectures

IEEE TRANSACTIONS ON INSTRUMENTATION AND MEASUREMENT (2023)

相关参考文献

注意：仅列出部分参考文献，下载原文获取全部文献信息。

Review Acoustics

A survey of sound source localization with deep learning methods

Pierre-Amaury Grumiaux et al.

Summary: This article presents a survey of deep learning methods for single and multiple sound source localization, specifically focusing on indoor environments with reverberation and diffuse noise. The article provides an extensive overview of the literature on neural network-based sound source localization, organized by neural network architecture, input features, output strategy, data types, and model training strategy. Tables summarizing the literature survey are provided for quick reference.

JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA (2022)

添加到收藏夹

Proceedings Paper Instruments & Instrumentation

Direction of Arrival Estimation of Moving Sound Sources using Deep Learning

Jana Rusrus et al.

Summary: In this paper, we evaluate the performance of a deep learning classification system for localization of moving sound sources, and investigate the effect of different hyperparameters and acoustic conditions. The study demonstrates the significance of hyperparameters and acoustic conditions in localizing high-speed sources.

2022 IEEE INTERNATIONAL INSTRUMENTATION AND MEASUREMENT TECHNOLOGY CONFERENCE (I2MTC 2022) (2022)

添加到收藏夹

Article Acoustics

Dynamically localizing multiple speakers based on the time-frequency domain

Hodaya Hammer et al.

Summary: This study introduces a deep neural network-based online multi-speaker localization algorithm that can accurately localize and track multiple speakers simultaneously, performing exceptionally well in both static and dynamic scenarios.

EURASIP JOURNAL ON AUDIO SPEECH AND MUSIC PROCESSING (2021)

添加到收藏夹

Article Acoustics

Robust Sound Source Tracking Using SRP-PHAT and 3D Convolutional Neural Networks

David Diaz-Guerra et al.

Summary: The article introduces a new single sound source DOA estimation and tracking system based on the SRP-PHAT algorithm and a three-dimensional Convolutional Neural Network, which accurately tracks sound sources even in highly reverberant scenarios. The system's causal architecture and new training procedure demonstrate its feasibility for real-time applications and robustness in various acoustic conditions. By using acoustical simulations and actual recordings, the system's good performance is proven even with low-resolution inputs.

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING (2021)

添加到收藏夹

Article Computer Science, Information Systems

nnAudio: An on-the-Fly GPU Audio to Spectrogram Conversion Toolbox Using 1D Convolutional Neural Networks

Kin Wai Cheuk et al.

IEEE ACCESS (2020)

添加到收藏夹

Article Engineering, Electrical & Electronic

Multi-Speaker DOA Estimation Using Deep Convolutional Networks Trained With Noise Signals

Soumitro Chakrabarty et al.

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (2019)

添加到收藏夹

Article Engineering, Electrical & Electronic

Sound Event Localization and Detection of Overlapping Sources Using Convolutional Recurrent Neural Networks

Sharath Adavanne et al.

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (2019)

添加到收藏夹

Article Engineering, Electrical & Electronic

CRNN-Based Multiple DoA Estimation Using Acoustic Intensity Features for Ambisonics Recordings

Laureline Perotin et al.

IEEE JOURNAL OF SELECTED TOPICS IN SIGNAL PROCESSING (2019)

添加到收藏夹

Proceedings Paper Computer Science, Hardware & Architecture

End-to-end Convolutional Neural Networks for Sound Event Detection in Urban Environments

Pablo Zinemanas et al.

PROCEEDINGS OF THE 24TH CONFERENCE OF OPEN INNOVATIONS ASSOCIATION (FRUCT) (2019)

添加到收藏夹

Proceedings Paper Acoustics

DEEP RANKING-BASED SOUND SOURCE LOCALIZATION

Renana Opochinsky et al.

2019 IEEE WORKSHOP ON APPLICATIONS OF SIGNAL PROCESSING TO AUDIO AND ACOUSTICS (WASPAA) (2019)

添加到收藏夹

Proceedings Paper Acoustics

POLYPHONIC SOUND EVENT DETECTION USING CONVOLUTIONAL BIDIRECTIONAL LSTM AND SYNTHETIC DATA-BASED TRANSFER LEARNING

Seokwon Jung et al.

2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (2019)

添加到收藏夹

Article Computer Science, Information Systems

Multitask Learning of Time-Frequency CNN for Sound Source Localization

Cheng Pang et al.

IEEE ACCESS (2019)

添加到收藏夹

Article Acoustics

Robust Binaural Localization of a Target Sound Source by Combining Spectral Source Models and Deep Neural Networks

Ning Ma et al.

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING (2018)

添加到收藏夹

Article Acoustics

Exploiting Deep Neural Networks and Head Movements for Robust Binaural Localization of Multiple Sources in Reverberant Environments

Ning Ma et al.

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING (2017)

添加到收藏夹

Article Acoustics

Convolutional Recurrent Neural Networks for Polyphonic Sound Event Detection

Emre Cakir et al.

IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING (2017)

添加到收藏夹

Proceedings Paper Computer Science, Artificial Intelligence

Temporal Convolutional Networks for Action Segmentation and Detection

Colin Lea et al.

30TH IEEE CONFERENCE ON COMPUTER VISION AND PATTERN RECOGNITION (CVPR 2017) (2017)

添加到收藏夹

Article Acoustics

Generating sensor signals in isotropic noise fields

Emanuel A. P. Habets et al.

JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA (2007)

添加到收藏夹

© Peeref 2019-2024. All rights reserved.