Papers Audio Classification
“Audio Classification” 태그가 달린 논문 413편 · 필터 해제
Conformer-Based Self-Supervised Learning for Non-Speech Audio Tasks
Representation learning from unlabeled data has been of major interest in artificial intelligence research. While self-supervised speech representation learning has been popular in the speech research community, very few…
Audio ClassificationRepresentation LearningSelf-Supervised LearningSpeech Representation LearningStudy of positional encoding approaches for Audio Spectrogram Transformers
Transformers have revolutionized the world of deep learning, specially in the field of natural language processing. Recently, the Audio Spectrogram Transformer (AST) was proposed for audio classification, leading to stat…
Audio ClassificationEfficient Training of Audio Transformers with Patchout
The great success of transformer-based models in natural language processing (NLP) has led to various attempts at adapting these architectures to other domains such as vision and audio. Recent work has shown that transfo…
Acoustic Scene ClassificationAudio ClassificationAudio TaggingGPU+1Rank-based loss for learning hierarchical representations
Hierarchical taxonomies are common in many contexts, and they are a very natural structure humans use to organise information. In machine learning, the family of methods that use the 'extra' information is called hierarc…
Audio ClassificationTripletSpliceOut: A Simple and Efficient Audio Augmentation Method
Time masking has become a de facto augmentation technique for speech and audio tasks, including automatic speech recognition (ASR) and audio classification, most notably as a part of SpecAugment. In this work, we propose…
Audio ClassificationAutomatic Speech RecognitionAutomatic Speech Recognition (ASR)Music Classification+4Audio Interval Retrieval using Convolutional Neural Networks
Modern streaming services are increasingly labeling videos based on their visual or audio content. This typically augments the use of technologies such as AI and ML by allowing to use natural speech for searching by keyw…
Audio ClassificationRetrievalSpeech-to-TextPruning vs XNOR-Net: A Comprehensive Study of Deep Learning for Audio Classification on Edge-devices
Deep learning has celebrated resounding successes in many application areas of relevance to the Internet of Things (IoT), such as computer vision and machine listening. These technologies must ultimately be brought direc…
Audio ClassificationClassificationDeep Learningimage-classification+4An empirical investigation into audio pipeline approaches for classifying bird species
This paper is an investigation into aspects of an audio classification pipeline that will be appropriate for the monitoring of bird species on edges devices. These aspects include transfer learning, data augmentation and…
Audio ClassificationClassificationData AugmentationModel Optimization+1Sparse Continuous Distributions and Fenchel-Young Losses
Exponential families are widely used in machine learning, including many distributions in continuous and discrete domains (e.g., Gaussian, Dirichlet, Poisson, and categorical distributions via the softmax transformation)…
Audio ClassificationQuestion AnsweringVisual Question AnsweringVisual Question Answering (VQA)Lung Sound Classification Using Co-tuning and Stochastic Normalization
In this paper, we use pre-trained ResNet models as backbone architectures for classification of adventitious lung sounds and respiratory diseases. The knowledge of the pre-trained model is transferred by using vanilla fi…
Audio ClassificationData AugmentationLung Sound ClassificationSound ClassificationA Multi-Head Relevance Weighting Framework For Learning Raw Waveform Audio Representations
In this work, we propose a multi-head relevance weighting framework to learn audio representations from raw waveforms. The audio waveform, split into windows of short duration, are processed with a 1-D convolutional laye…
Audio ClassificationSound ClassificationTemporal-wise Attention Spiking Neural Networks for Event Streams Classification
How to effectively and efficiently deal with spatio-temporal event streams, where the events are generally sparse and non-uniform and have the microsecond temporal resolution, is of great value and has various real-life …
Audio ClassificationClassificationGesture Recognitionimage-classification+1On the Veracity of Local, Model-agnostic Explanations in Audio Classification: Targeted Investigations with Adversarial Examples
Local explanation methods such as LIME have become popular in MIR as tools for generating post-hoc, model-agnostic explanations of a model's classification decisions. The basic idea is to identify a small set of human-un…
Audio ClassificationOver-Parameterization and Generalization in Audio Classification
Convolutional Neural Networks (CNNs) have been dominating classification tasks in various domains, such as machine vision, machine listening, and natural language processing. In machine listening, while generally exhibit…
Acoustic Scene ClassificationAudio ClassificationClassificationScene ClassificationFederated Self-Training for Semi-Supervised Audio Recognition
Federated Learning is a distributed machine learning paradigm dealing with decentralized and personal datasets. Since data reside on devices like smartphones and virtual assistants, labeling is entrusted to the clients, …
Audio ClassificationFederated LearningWeakly-Supervised Classification and Detection of Bird Sounds in the Wild.
It is easier to hear birds than see them, however, they still play an essential role in nature and they are excellent indicators of deteriorating environmental quality and pollution. Recent advances in Machine Learning a…
Audio ClassificationAudio TaggingBird Audio DetectionSound Event Detection+1Attention Bottlenecks for Multimodal Fusion
Humans perceive the world by concurrently processing and fusing high-dimensional inputs from multiple modalities such as vision and audio. Machine perception models, in stark contrast, are typically modality-specific and…
Action ClassificationAction RecognitionAudio ClassificationVideo ClassificationDCASE 2021 Task 3: Spectrotemporally-aligned Features for Polyphonic Sound Event Localization and Detection
Sound event localization and detection consists of two subtasks which are sound event detection and direction-of-arrival estimation. While sound event detection mainly relies on time-frequency patterns to distinguish dif…
Audio ClassificationDirection of Arrival EstimationEvent DetectionSound Event Detection+1On fine-tuning of Autoencoders for Fuzzy rule classifiers
Recent discoveries in Deep Neural Networks are allowing researchers to tackle some very complex problems such as image classification and audio classification, with improved theoretical and empirical justifications. This…
Audio ClassificationClassificationimage-classificationImage ClassificationZero-Shot Federated Learning with New Classes for Audio Classification
Federated learning is an effective way of extracting insights from different user devices while preserving the privacy of users. However, new classes with completely unseen data distributions can stream across any device…
Audio ClassificationClassificationClusteringFederated Learning+2