Papers Audio Classification
“Audio Classification” 태그가 달린 논문 413편 · 필터 해제
Simultaneously Learning Architectures and Features of Deep Neural Networks
This paper presents a novel method which simultaneously learns the number of filters and network features repeatedly over multiple epochs. We propose a novel pruning loss to explicitly enforces the optimizer to focus on …
Audio ClassificationClassificationDiversityGeneral Classification+3CNN depth analysis with different channel inputs for Acoustic Scene Classification
Acoustic scene classification (ASC) has been approached in the last years using deep learning techniques such as convolutional neural networks or recurrent neural networks. Many state-of-the-art solutions are based on im…
Acoustic Scene ClassificationAudio ClassificationGeneral Classificationimage-classification+2Unified Probabilistic Deep Continual Learning through Generative Replay and Open Set Recognition
Modern deep neural networks are well known to be brittle in the face of unknown data instances and recognition of the latter remains a challenge. Although it is inevitable for continual-learning systems to encounter such…
Audio ClassificationBayesian InferenceContinual LearningOpen Set Learning+1Zero-Shot Audio Classification Based on Class Label Embeddings
This paper proposes a zero-shot learning approach for audio classification based on the textual information about class labels without any audio samples from target classes. We propose an audio classification system buil…
Audio ClassificationClassificationGeneral ClassificationZero-shot Audio Classification+1A Robust Approach for Securing Audio Classification Against Adversarial Attacks
Adversarial audio attacks can be considered as a small perturbation unperceptive to human ears that is intentionally added to the audio signal and causes a machine learning model to make mistakes. This poses a security c…
Audio ClassificationBIG-bench Machine LearningClassificationDimensionality Reduction+1Audio-Visual Model Distillation Using Acoustic Images
In this paper, we investigate how to learn rich and robust feature representations for audio classification from visual data and acoustic images, a novel audio data modality. Former models learn audio representations fro…
Action RecognitionAudio ClassificationGeneral Classificationmodel+2Audio Classification of Bit-Representation Waveform
This study investigated the waveform representation for audio signal classification. Recently, many studies on audio waveform classification such as acoustic event detection and music genre classification have been publi…
Audio ClassificationClassificationEvent DetectionGeneral Classification+3Improving performance and inference on audio classification tasks using capsule networks
Classification of audio samples is an important part of many auditory systems. Deep learning models based on the Convolutional and the Recurrent layers are state-of-the-art in many such tasks. In this paper, we approach …
Audio ClassificationClassificationGeneral ClassificationMulti-Label Classification+2Context, Attention and Audio Feature Explorations for Audio Visual Scene-Aware Dialog
With the recent advancements in AI, Intelligent Virtual Assistants (IVA) have become a ubiquitous part of every home. Going forward, we are witnessing a confluence of vision, speech and dialog system technologies that ar…
Audio ClassificationGeneral ClassificationCross-domain Deep Feature Combination for Bird Species Classification with Audio-visual Data
In recent decade, many state-of-the-art algorithms on image classification as well as audio classification have achieved noticeable successes with the development of deep convolutional neural network (CNN). However, most…
Audio ClassificationBird Species Classification With Audio-Visual DataGeneral Classificationimage-classification+2AclNet: efficient end-to-end audio classification CNN
We propose an efficient end-to-end convolutional neural network architecture, AclNet, for audio classification. When trained with our data augmentation and regularization, we achieved state-of-the-art performance on the …
Audio ClassificationClassificationData AugmentationGeneral ClassificationUbicoustics: Plug-and-Play Acoustic Activity Recognition
Despite sound being a rich source of information, computing devices with microphones do not leverage audio to glean useful insights about their physical and social context. For example, a smart speaker sitting on a kitch…
Activity RecognitionAudio ClassificationData AugmentationEnvironmental Sound Classification+1AudioMNIST: Exploring Explainable Artificial Intelligence for Audio Analysis on a Simple Benchmark
Explainable Artificial Intelligence (XAI) is targeted at understanding how models perform feature selection and derive their classification decisions. This paper explores post-hoc explanations for deep neural networks in…
Audio ClassificationDecision MakingExplainable artificial intelligenceExplainable Artificial Intelligence (XAI)+2Cooperative Learning of Audio and Video Models from Self-Supervised Synchronization
There is a natural correlation between the visual and auditive elements of a video. In this work we leverage this connection to learn general and effective models for both audio and video analysis from self-supervised te…
Action RecognitionAudio ClassificationSelf-Supervised Action RecognitionSelf-Supervised Audio Classification+1A Closer Look at Weak Label Learning for Audio Events
Audio content analysis in terms of sound events is an important research problem for a variety of applications. Recently, the development of weak labeling approaches for audio or sound event detection (AED) and availabil…
Audio ClassificationEvent DetectionSound Event DetectionWeakly-supervised LearningMasked Conditional Neural Networks for Audio Classification
We present the ConditionaL Neural Network (CLNN) and the Masked ConditionaL Neural Network (MCLNN) designed for temporal signal recognition. The CLNN takes into consideration the temporal nature of the sound signal and t…
Audio ClassificationClassificationGeneral ClassificationMulti-level Attention Model for Weakly Supervised Audio Classification
In this paper, we propose a multi-level attention model to solve the weakly labelled audio classification problem. The objective of audio classification is to predict the presence or absence of audio events in an audio c…
Audio ClassificationWSNet: Learning Compact and Efficient Networks with 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 t…
Audio ClassificationGeneral ClassificationPaper generationQuantizationRepresentations of Sound in Deep Learning of Audio Features from Music
The work of a single musician, group or composer can vary widely in terms of musical style. Indeed, different stylistic elements, from performance medium and rhythm to harmony and texture, are typically exploited and dev…
Audio ClassificationGeneral ClassificationRhythmRaw Waveform-based Audio Classification Using Sample-level CNN Architectures
Music, speech, and acoustic scene sound are often handled separately in the audio domain because of their different signal characteristics. However, as the image domain grows rapidly by versatile image classification mod…
Audio ClassificationClassificationGeneral Classificationimage-classification+1