Papers Audio Classification
“Audio Classification” 태그가 달린 논문 413편 · 필터 해제
Learning Sparse Adversarial Dictionaries For Multi-Class Audio Classification
Audio events are quite often overlapping in nature, and more prone to noise than visual signals. There has been increasing evidence for the superior performance of representations learned using sparse dictionaries for ap…
Audio ClassificationAudio DenoisingClassificationDenoising+3WSNet: Compact and Efficient Networks Through Weight Sampling
We present a new approach and a novel architecture, termed WSNet, for learning compact and efficient deep neural networks. Existing approaches conventionally learn full model parameters independently and then compress th…
Audio ClassificationGeneral ClassificationQuantizationFearNet: Brain-Inspired Model for Incremental Learning
Incremental class learning involves sequentially learning classes in bursts of examples from the same class. This violates the assumptions that underlie methods for training standard deep neural networks, and will cause …
Audio ClassificationIncremental LearningmodelUnsupervised Learning of Semantic Audio Representations
Even in the absence of any explicit semantic annotation, vast collections of audio recordings provide valuable information for learning the categorical structure of sounds. We consider several class-agnostic semantic con…
Audio ClassificationClassificationGeneral ClassificationRetrieval+1Comparison of Time-Frequency Representations for Environmental Sound Classification using Convolutional Neural Networks
Recent successful applications of convolutional neural networks (CNNs) to audio classification and speech recognition have motivated the search for better input representations for more efficient training. Visual display…
Audio ClassificationClassificationEnvironmental Sound ClassificationGeneral Classification+3Look, Listen and Learn
We consider the question: what can be learnt by looking at and listening to a large number of unlabelled videos? There is a valuable, but so far untapped, source of information contained in the video itself -- the corres…
Audio ClassificationGeneral ClassificationSound ClassificationCNN Architectures for Large-Scale Audio Classification
Convolutional Neural Networks (CNNs) have proven very effective in image classification and show promise for audio. We use various CNN architectures to classify the soundtracks of a dataset of 70M training videos (5.24 m…
Audio ClassificationEvent DetectionGeneral Classificationimage-classificationConvolutional RNN: an Enhanced Model for Extracting Features from Sequential Data
Traditional convolutional layers extract features from patches of data by applying a non-linearity on an affine function of the input. We propose a model that enhances this feature extraction process for the case of sequ…
Audio ClassificationA Deep Bag-of-Features Model for Music Auto-Tagging
Feature learning and deep learning have drawn great attention in recent years as a way of transforming input data into more effective representations using learning algorithms. Such interest has grown in the area of musi…
Audio ClassificationInformation RetrievalMusic Auto-TaggingMusic Information Retrieval+2Unsupervised Structure Discovery for Semantic Analysis of Audio
Approaches to audio classification and retrieval tasks largely rely on detection-based discriminative models. We submit that such models make a simplistic assumption in mapping acoustics directly to semantics, whereas th…
Audio ClassificationGeneral ClassificationRetrievalFast Labeling and Transcription with the Speechalyzer Toolkit
We describe a software tool named Speechalyzer which is optimized to process large speech data sets with respect to transcription, labeling and annotation. It is implemented as a client server based framework in Java a…
Audio ClassificationBenchmarkingClassificationGeneral Classification+6Sparse Filtering
Unsupervised feature learning has been shown to be effective at learning representations that perform well on image, video and audio classification. However, many existing feature learning algorithms are hard to use and …
Audio ClassificationClassificationGeneral ClassificationUnsupervised feature learning for audio classification using convolutional deep belief networks
In recent years, deep learning approaches have gained significant interest as a way of building hierarchical representations from unlabeled data. However, to our knowledge, these deep learning approaches have not been ex…
Audio ClassificationDeep LearningGeneral Classification