標題: Titlebook: Computational Analysis of Sound Scenes and Events; Tuomas Virtanen,Mark D. Plumbley,Dan Ellis Book 2018 Springer International Publishing [打印本頁] 作者: Entangle 時間: 2025-3-21 17:38
書目名稱Computational Analysis of Sound Scenes and Events影響因子(影響力)
書目名稱Computational Analysis of Sound Scenes and Events影響因子(影響力)學科排名
書目名稱Computational Analysis of Sound Scenes and Events網絡公開度
書目名稱Computational Analysis of Sound Scenes and Events網絡公開度學科排名
書目名稱Computational Analysis of Sound Scenes and Events被引頻次
書目名稱Computational Analysis of Sound Scenes and Events被引頻次學科排名
書目名稱Computational Analysis of Sound Scenes and Events年度引用
書目名稱Computational Analysis of Sound Scenes and Events年度引用學科排名
書目名稱Computational Analysis of Sound Scenes and Events讀者反饋
書目名稱Computational Analysis of Sound Scenes and Events讀者反饋學科排名
作者: heirloom 時間: 2025-3-21 21:48
Everyday Sound Categorizationn, synthesizing the main findings of studies on isolated sound events as well as complex sound scenes. Finally, we review recently proposed taxonomies for everyday sounds and conclude by providing directions for integrating insights from cognitive psychology into the design and evaluation of computational systems.作者: QUAIL 時間: 2025-3-22 02:48
Multiview Approaches to Event Detection and Scene Analysislevel presentation of generic methods that are particularly relevant in the context of multiview and multimodal sound scene analysis. Then, we more specifically present a selection of techniques used for audiovisual event detection and microphone array-based scene analysis.作者: 防御 時間: 2025-3-22 06:05
Peter Kraemer,Claus-Peter Fritzen content analysis fields such as automatic speech recognition and music information retrieval. We discuss the main challenges in the field, and give a short historical perspective of the development of the field. We also shortly summarize the role of each chapter in the book.作者: 船員 時間: 2025-3-22 10:47 作者: 概觀 時間: 2025-3-22 13:45 作者: 概觀 時間: 2025-3-22 18:30 作者: Ptosis 時間: 2025-3-22 23:21
The Machine Learning Approach for Analysis of Sound Scenes and Eventsing, feature extraction, and pattern classification. We also preset an example system based on multi-label deep neural networks, which has been found to be applicable in many analysis tasks discussed in this book. Finally, we explain the whole processing chain that involves developing computational audio analysis systems.作者: Exonerate 時間: 2025-3-23 05:17 作者: 無聊點好 時間: 2025-3-23 09:05 作者: 墊子 時間: 2025-3-23 13:31
Laura Murray,Deanna Kerrigan,Vera PaivaWe then describe modern deep learning architectures, including convolutional networks, different variants of recurrent neural networks, and hybrid models. Finally, we survey model-agnostic techniques for improving the stability of classifiers.作者: ARENA 時間: 2025-3-23 16:53 作者: 卷發(fā) 時間: 2025-3-23 20:37
William G. Faris,Giovanni Jona-Lasinioand how a combination of convolutional networks and data augmentation result in the current state of the art. We close with a discussion about the potential and challenges of mobile sensing, the limitations imposed by the data currently available for research, and a few areas for future exploration.作者: Incorporate 時間: 2025-3-24 00:52 作者: indecipherable 時間: 2025-3-24 04:43 作者: 先鋒派 時間: 2025-3-24 08:55
Sound Analysis in Smart Citiesand how a combination of convolutional networks and data augmentation result in the current state of the art. We close with a discussion about the potential and challenges of mobile sensing, the limitations imposed by the data currently available for research, and a few areas for future exploration.作者: 懦夫 時間: 2025-3-24 14:26 作者: paragon 時間: 2025-3-24 18:33 作者: 要塞 時間: 2025-3-24 22:38
https://doi.org/10.1007/978-1-4419-9834-7level presentation of generic methods that are particularly relevant in the context of multiview and multimodal sound scene analysis. Then, we more specifically present a selection of techniques used for audiovisual event detection and microphone array-based scene analysis.作者: Introvert 時間: 2025-3-24 23:24 作者: animated 時間: 2025-3-25 04:18
d.Covers all the aspects of the machine learning approach to.This book presents computational methods for extracting the useful information from audio signals, collecting the state of the art in the field of sound event and scene analysis. The authors cover the entire procedure for developing such m作者: Ganglion 時間: 2025-3-25 09:26 作者: 大雨 時間: 2025-3-25 14:46 作者: 文藝 時間: 2025-3-25 19:48
Acoustics and Psychoacoustics of Sound Scenes and Eventscoustic information reaching the listeners’ ears. Despite the complexity of the signal, human listeners . effortlessly these scenes into different .. This chapter provides an overview of the auditory mechanisms subserving this ability. First, we briefly introduce the major characteristics of sound p作者: fulcrum 時間: 2025-3-25 21:18 作者: antidote 時間: 2025-3-26 03:40
Statistical Methods for Scene and Event Classificationically the raw waveform or a time-frequency spectrogram, and produce semantically meaningful classification of its contents. We begin with a brief overview of statistical modeling, supervised machine learning, and model validation. This is followed by a survey of discriminative models for binary and作者: 無聊點好 時間: 2025-3-26 07:16
Datasets and Evaluationvaluation procedure for a classification or recognition system will involve a standard dataset of example input data along with the intended target output, and well-defined metrics to compare the systems’ outputs with this ground truth. This chapter examines the important factors in the design and c作者: POWER 時間: 2025-3-26 10:30 作者: 取消 時間: 2025-3-26 16:13 作者: preeclampsia 時間: 2025-3-26 19:54
Multiview Approaches to Event Detection and Scene Analysis, each sensor contributing a particular . of the data (e.g., audio microphones, video cameras, etc.). We briefly introduce some of the techniques that can be exploited to effectively combine the data conveyed by the different views under analysis for a better interpretation. We first provide a high-作者: 殖民地 時間: 2025-3-26 23:06
Sound Sharing and Retrieval sharing sites in which users can search, browse, and contribute large amounts of audio content such as sound effects, field and urban recordings, music tracks, and music samples. This poses many challenges to enable search, discovery, and ultimately reuse of this content. In this chapter we give an作者: 流逝 時間: 2025-3-27 01:41 作者: ANNUL 時間: 2025-3-27 05:46 作者: cartilage 時間: 2025-3-27 11:06
Sound Analysis in Smart Citieswide range of applications for the computational analysis of urban sounds and focuses on two high-impact areas, audio surveillance, and noise pollution monitoring, which sit at the intersection of dense sensor networks and machine listening. For sensor networks we focus on the pros and cons of mobil作者: 無聊點好 時間: 2025-3-27 14:51 作者: 黃瓜 時間: 2025-3-27 18:42
Peter Kraemer,Claus-Peter Fritzenovel methods have been proposed to analyze this information automatically, and several new applications have emerged. This chapter introduces the basic concepts and research problems and engineering challenges in computational environmental sound analysis. We motivate the field by briefly describing作者: craving 時間: 2025-3-27 22:28
https://doi.org/10.1007/978-3-319-69305-7 applications seem different, the underlying computational methods are typically based on the same principles. We explain the commonalities between analysis tasks such as sound event detection, sound scene classification, or audio tagging. We focus on the machine learning approach, where the sound c作者: Fulsome 時間: 2025-3-28 04:53
https://doi.org/10.1007/978-3-319-69305-7coustic information reaching the listeners’ ears. Despite the complexity of the signal, human listeners . effortlessly these scenes into different .. This chapter provides an overview of the auditory mechanisms subserving this ability. First, we briefly introduce the major characteristics of sound p作者: Dna262 時間: 2025-3-28 07:53 作者: ALB 時間: 2025-3-28 10:58 作者: 饒舌的人 時間: 2025-3-28 18:38
Deanna Kerrigan,Clare Barringtonvaluation procedure for a classification or recognition system will involve a standard dataset of example input data along with the intended target output, and well-defined metrics to compare the systems’ outputs with this ground truth. This chapter examines the important factors in the design and c作者: 大方不好 時間: 2025-3-28 22:12
Christoph Butenweg,Britta Holtschoppengories to make sense of their environment. We begin with an overview of prominent theories of categorization in the psychological literature, followed by data collection and analysis methods used in empirical research on categorization with human participants. We then focus on auditory categorizatio作者: IDEAS 時間: 2025-3-29 02:57 作者: 松馳 時間: 2025-3-29 04:23 作者: Morose 時間: 2025-3-29 08:46
Structural Electron Crystallography sharing sites in which users can search, browse, and contribute large amounts of audio content such as sound effects, field and urban recordings, music tracks, and music samples. This poses many challenges to enable search, discovery, and ultimately reuse of this content. In this chapter we give an作者: 完成 時間: 2025-3-29 12:16 作者: Temporal-Lobe 時間: 2025-3-29 18:25
Crystallization and Data Collectioneviews three aspects of the productization of AER which are important to consider when developing pathways to impact between fundamental research and “real-world” applicative outlets. In the first section, it is shown that applications introduce a variety of practical constraints which elicit new re作者: 定點 時間: 2025-3-29 23:43 作者: 喚醒 時間: 2025-3-30 00:18 作者: laceration 時間: 2025-3-30 07:03
Tuomas Virtanen,Mark D. Plumbley,Dan EllisGives an overview of methods for computational analysis of sounds scenes and events, allowing those new to the field to become fully informed.Covers all the aspects of the machine learning approach to作者: GET 時間: 2025-3-30 11:45 作者: JOG 時間: 2025-3-30 15:26 作者: 公司 時間: 2025-3-30 18:46 作者: CORE 時間: 2025-3-30 22:48
