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Audio Classification Question Answering 404 Semantic Segmentation 342 Object Detection 321 Image Classification 279 Classification 206 Text Generation 171 Language Modelling 165 Text Classification 157 Visual Question Answering (VQA) 143 Named Entity Recognition (NER) 129 Pose Estimation 123 Anomaly Detection 119 Action Recognition 114 Instance Segmentation 107 Sentiment Analysis 104 Text Summarization 97 Reading Comprehension 95 Domain Adaptation 94 Speech Recognition 94 2D Object Detection 91 Information Retrieval 91 Image Retrieval 86 Machine Translation 83 Natural Language Inference 81 Relation Extraction 80 Image Generation 78 Image Captioning 77 Depth Estimation 76 Node Classification 76 2D Semantic Segmentation 75 Natural Language Understanding 71 Autonomous Driving 69 Face Recognition 67 Link Prediction 67 Object Tracking 67 Person Re-Identification 66 3D Object Detection 65 Data Augmentation 63 Code Generation 62 Multi-Task Learning 59 3D Reconstruction 57 Common Sense Reasoning 56 Recommendation Systems 56 Abstractive Text Summarization 53 Graph Classification 53 Optical Character Recognition (OCR) 53 Video Understanding 53 Word Embeddings 53 Medical Image Segmentation 51 3D Human Pose Estimation 50 Emotion Recognition 48 Hate Speech Detection 46 Knowledge Graphs 46 Self-Supervised Learning 46 Coreference Resolution 45 Few-Shot Learning 45 Object Recognition 45 Semantic Parsing 45 Time Series Forecasting 45 Image Clustering 44 Visual Reasoning 44 Entity Linking 43 Image Super-Resolution 43 Machine Reading Comprehension 43 Misinformation 43 Scene Understanding 43 Zero-Shot Learning 43 Multi-Object Tracking 42 Temporal Action Localization 42 Fine-Grained Image Classification 41 Video Question Answering 41 3D Semantic Segmentation 40 Decision Making 40 Face Detection 39 Image Segmentation 39 Novel View Synthesis 39 Segmentation 38 Video Captioning 38 3D Pose Estimation 36 Panoptic Segmentation 36 Continual Learning 35 Optical Flow Estimation 35 Stance Detection 35 Trajectory Prediction 35 Video Retrieval 35 Action Detection 34 Retrieval 34 Text Retrieval 34 Action Classification 32 Automatic Speech Recognition (ASR) 32 Dialogue Generation 32 Image-to-Image Translation 32 Metric Learning 32 Monocular Depth Estimation 32 Music Generation 32 Unsupervised Domain Adaptation 32 Visual Question Answering 32 Activity Recognition 30 Domain Generalization 30 Fake News Detection 30 Skeleton Based Action Recognition 30 Autonomous Vehicles 29 Facial Expression Recognition (FER) 29 Multi-Label Classification 29 Scene Text Recognition 29 Visual Object Tracking 29 Document Summarization 28 Object Counting 28 Neural Architecture Search 27 Sign Language Recognition 27 Unsupervised Anomaly Detection 27 Visual Tracking 27 regression 27 Drug Discovery 26 Music Information Retrieval 26 Open-Domain Question Answering 26 Part-Of-Speech Tagging 26 Slot Filling 26 Visual Odometry 26 2D Human Pose Estimation 25 DeepFake Detection 25 Emotion Classification 25 Few-Shot Image Classification 25 NER 25 Visual Localization 25 Data-to-Text Generation 24 Face Verification 24 Intent Detection 24 Text-to-Image Generation 24 Time Series Analysis 24 Video Prediction 24 Visual Place Recognition 24 Cross-Modal Retrieval 23 Denoising 23 Fairness 23 Hand Pose Estimation 23 Low-Light Image Enhancement 23 Out-of-Distribution Detection 23 6D Pose Estimation 22 Cell Segmentation 22 Crowd Counting 22 Human-Object Interaction Detection 22 Math Word Problem Solving 22 Multimodal Deep Learning 22 Question Generation 22 Relation Classification 22 Scene Classification 22 Speech Synthesis 22 Graph Regression 21 Handwriting Recognition 21 Image Denoising 21 Imitation Learning 21 Mathematical Reasoning 21 Medical Diagnosis 21 Molecular Property Prediction 21 Robotic Grasping 21 Simultaneous Localization and Mapping 21 Super-Resolution 21 Video Classification 21 3D Hand Pose Estimation 20 Age Estimation 20 Aspect-Based Sentiment Analysis (ABSA) 20 Image Manipulation Detection 20 Sound Event Detection 20 Speech Emotion Recognition 20 Speech Enhancement 20 Stereo Matching 20 Style Transfer 20 Task-Oriented Dialogue Systems 20 Text-To-SQL 20 Traffic Prediction 20 Video Generation 20 Animal Pose Estimation 19 Graph Clustering 19 Language Identification 19 Medical Image Classification 19 Motion Synthesis 19 Reinforcement Learning (RL) 19 Text Simplification 19 18 Document Classification 18 Image Enhancement 18 Logical Reasoning 18 Meta-Learning 18 Paraphrase Identification 18 Quantization 18 Semantic Textual Similarity 18 Text-To-Speech Synthesis 18 Time Series Classification 18 Transductive Zero-Shot Classification 18 Visual Navigation 18 Zero-Shot Video Question Answer 18 3D Instance Segmentation 17 Action Recognition In Videos 17 Action Segmentation 17 Beat Tracking 17 Binarization 17 Change Detection 17 Fact Verification 17 Gaze Estimation 17 Lane Detection 17 Motor Imagery Decoding (left-hand vs right-hand) 17 Multivariate Time Series Forecasting 17 Named Entity Recognition 17 Object Localization 17 Pedestrian Detection 17 Robot Navigation 17 SMAC+ 17 Salient Object Detection 17 Scene Text Detection 17 Topic Models 17 Transfer Learning 17 Translation 17 Video Anomaly Detection 17 Video Object Segmentation 17 3D Object Tracking 16 Binary Classification 16 Face Alignment 16 Face Anti-Spoofing 16 Grammatical Error Correction 16 Image Dehazing 16 Image Inpainting 16 Image Restoration 16 Knowledge Graph Completion 16 Learning with noisy labels 16 Long-tail Learning 16 Multiple Object Tracking 16 Paraphrase Generation 16 Prompt Engineering 16 RGB Salient Object Detection 16 Scene Recognition 16 Sign Language Translation 16 Speech Separation 16 Time Series 16 Video Summarization 16 Video Super-Resolution 16 3D Human Reconstruction 15 Active Learning 15 Audio Source Separation 15 Automatic Speech Recognition 15 Computed Tomography (CT) 15 Contrastive Learning 15 Cross-Lingual Transfer 15 Deblurring 15 Facial Landmark Detection 15 Hand Gesture Recognition 15 Knowledge Base Question Answering 15 Lesion Segmentation 15 Node Classification on Non-Homophilic (Heterophilic) Graphs 15 Node Clustering 15 Self-Driving Cars 15 Semantic Similarity 15 Video Frame Interpolation 15 Weather Forecasting 15 Within-Session ERP 15 Zero-shot Text Search 15 3D Action Recognition 14 3D Classification 14 Boundary Detection 14 Code Search 14 Dependency Parsing 14 Event Extraction 14 Gesture Recognition 14 Hierarchical Multi-label Classification 14 Instruction Following 14 Joint Entity and Relation Extraction 14 License Plate Recognition 14 Multi-Document Summarization 14 Open Information Extraction 14 Sarcasm Detection 14 Semantic Role Labeling 14 Sentiment Classification 14 Single-View 3D Reconstruction 14 Spoken Language Understanding 14 Trajectory Forecasting 14 Tumor Segmentation 14 Word Sense Disambiguation 14 2D Pose Estimation 13 Adversarial Robustness 13 Clustering Algorithms Evaluation 13 Density Estimation 13 Emotion Recognition in Conversation 13 Handwritten Text Recognition 13 Human Activity Recognition 13 Human Detection 13 Hyperspectral Image Classification 13 Image Quality Assessment 13 Intent Classification 13 Keypoint Detection 13 Multiple Instance Learning 13 Music Transcription 13 Open-Domain Dialog 13 Physical Simulations 13 Pose Tracking 13 Saliency Detection 13 Semi-Supervised Image Classification 13 Semi-Supervised Semantic Segmentation 13 Semi-Supervised Video Object Segmentation 13 Sentence Classification 13 Small Object Detection 13 UIE 13 Weakly Supervised Object Detection 13 Activity Detection 12 Code Completion 12 Community Detection 12 Disentanglement 12 Document Layout Analysis 12 Event Detection 12 Fraud Detection 12 Image Compression 12 Image Registration 12 Imputation 12 Indoor Localization 12 Multi-class Classification 12 Text-to-Video Generation 12 Video Object Tracking 12 Video Quality Assessment 12 Vision and Language Navigation 12 motion prediction 12 3D Face Reconstruction 11 Adversarial Attack 11 Audio Generation 11 Bias Detection 11 Conversational Response Selection 11 Dialogue State Tracking 11 Downbeat Tracking 11 Event-based vision 11 Generalizable Person Re-identification 11 Image Reconstruction 11 Medical Visual Question Answering 11 Motion Forecasting 11 Multi-Label Text Classification 11 Network Intrusion Detection 11 Real-Time Semantic Segmentation 11 Referring Expression Comprehension 11 Relational Reasoning 11 Speaker Verification 11 Stochastic Optimization 11 Surface Normals Estimation 11 Time Series Prediction 11 Video Inpainting 11 Video Segmentation 11 Acoustic Scene Classification 10 Action Anticipation 10 Answer Selection 10 Audio Tagging 10 Automatic Post-Editing 10 Binary text classification 10 COVID-19 Diagnosis 10 Chatbot 10 Depth Completion 10 Entity Disambiguation 10 Entity Typing 10 Facial Attribute Classification 10 Fact Checking 10 Fine-Grained Image Recognition 10 Graph Embedding 10 Head Pose Estimation 10 Image Manipulation 10 License Plate Detection 10 Material Recognition 10 Mathematical Question Answering 10 Nested Named Entity Recognition 10 News Classification 10 Object Detection In Indoor Scenes 10 Opinion Mining 10 Outlier Detection 10 Referring Expression Segmentation 10 Scene Graph Generation 10 Sentence Embeddings 10 Table annotation 10 Unsupervised Object Segmentation 10 Video Object Detection 10 Virtual Try-on 10 Zero-Shot Composed Image Retrieval (ZS-CIR) 10 3D Depth Estimation 9 3D Medical Imaging Segmentation 9 3D Shape Reconstruction 9 6D Pose Estimation using RGBD 9 Abusive Language 9 Action Quality Assessment 9 Blind Super-Resolution 9 Citation Recommendation 9 Column Type Annotation 9 Conversational Question Answering 9 Dimensionality Reduction 9 Discourse Parsing 9 Entity Resolution 9 Federated Learning 9 Few-Shot Audio Classification 9 Graph Learning 9 Graph Matching 9 Handwriting generation 9 Key Information Extraction 9 Multi-Label Image Classification 9 Multiple-choice 9 Multiview Detection 9 Object Detection In Aerial Images 9 Person Identification 9 Point Cloud Registration 9 Reinforcement Learning 9 Robot Manipulation 9 Scene Generation 9 Speaker Diarization 9 Time Series Anomaly Detection 9 Topic Classification 9 Unsupervised Person Re-Identification 9 Video Recognition 9 Visual Dialog 9 Visual Grounding 9 Within-Session Motor Imagery (left hand vs. right hand) 9 3D Object Recognition 8 Ad-hoc video search 8 Arithmetic Reasoning 8 AutoML 8 Automated Theorem Proving 8 Breast Cancer Detection 8 Causal Inference 8 Change Point Detection 8 Chart Question Answering 8 Conditional Image Generation 8 Continuous Control 8 Cross-Lingual NER 8 Defect Detection 8 Dense Video Captioning 8 Disaster Response 8 ECG Classification 8 Edge Detection 8 Explanation Generation 8 Fine-Grained Visual Recognition 8 Gait Recognition 8 General Classification 8 Generalized Zero-Shot Learning 8 Human Part Segmentation 8 Incremental Learning 8 LIDAR Semantic Segmentation 8 Medical Image Registration 8 Medical Report Generation 8 Multi-Label Learning 8 Multi-agent Reinforcement Learning 8 Music Classification 8 Music Source Separation 8 Online Multi-Object Tracking 8 Passage Retrieval 8 Person Search 8 Remote Sensing Image Classification 8 Robust classification 8 Satellite Image Classification 8 Scene Segmentation 8 Sequential Recommendation 8 Shadow Removal 8 Sound Event Localization and Detection 8 Table Detection 8 Temporal Tagging 8 Text-to-Code Generation 8 Time Series Regression 8 Unsupervised Object Detection 8 Unsupervised Video Object Segmentation 8 Vehicle Re-Identification 8 Video Reconstruction 8 object-detection 8 3D Human Shape Estimation 7 3D Object Reconstruction 7 3D Shape Modeling 7 6D Pose Estimation using RGB 7 Anomaly Detection In Surveillance Videos 7 Argument Mining 7 Audio-Visual Speech Recognition 7 Bayesian Inference 7 Benchmarking 7 Camera Localization 7 Camouflaged Object Segmentation 7 Chinese Reading Comprehension 7 Click-Through Rate Prediction 7 Code Classification 7 Code Translation 7 Color Image Denoising 7 Conversational Response Generation 7 Correlated Time Series Forecasting 7 Data Integration 7 Dialogue Understanding 7 Dynamic Link Prediction 7 Electroencephalogram (EEG) 7 Face Identification 7 Face Swapping 7 Font Recognition 7 Food Recognition 7 Gender Prediction 7 Heterogeneous Node Classification 7 Homography Estimation 7 Human Interaction Recognition 7 Image Manipulation Localization 7 Interactive Segmentation 7 KG-to-Text Generation 7 Keyword Spotting 7 Monocular Visual Odometry 7 Motion Estimation 7 Multimodal Emotion Recognition 7 Multimodal Reasoning 7
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40 dataset results for Audio Classification

AudioSet

Audioset is an audio event dataset, which consists of over 2M human-annotated 10-second video clips. These clips are collected from YouTube, therefore many of which are in poor-quality and contain multiple sound-sources. A hierarchical ontology of 632 event classes is employed to annotate these data, which means that the same sound could be annotated as different labels. For example, the sound of barking is annotated as Animal, Pets, and Dog. All the videos are split into Evaluation/Balanced-Train/Unbalanced-Train set.

700 PAPERS • 6 BENCHMARKS

Common Voice

Common Voice is an audio dataset that consists of a unique MP3 and corresponding text file. There are 9,283 recorded hours in the dataset. The dataset also includes demographic metadata like age, sex, and accent. The dataset consists of 7,335 validated hours in 60 languages.

412 PAPERS • 80 BENCHMARKS

Speech Commands

Speech Commands is an audio dataset of spoken words designed to help train and evaluate keyword spotting systems .

375 PAPERS • 4 BENCHMARKS

ESC-50

The ESC-50 dataset is a labeled collection of 2000 environmental audio recordings suitable for benchmarking methods of environmental sound classification. It comprises 2000 5s-clips of 50 different classes across natural, human and domestic sounds, again, drawn from Freesound.org.

365 PAPERS • 8 BENCHMARKS

VGG-Sound

Consists of more than 210k videos for 310 audio classes.

197 PAPERS • 4 BENCHMARKS

EPIC-KITCHENS-100

This paper introduces the pipeline to scale the largest dataset in egocentric vision EPIC-KITCHENS. The effort culminates in EPIC-KITCHENS-100, a collection of 100 hours, 20M frames, 90K actions in 700 variable-length videos, capturing long-term unscripted activities in 45 environments, using head-mounted cameras. Compared to its previous version (EPIC-KITCHENS-55), EPIC-KITCHENS-100 has been annotated using a novel pipeline that allows denser (54% more actions per minute) and more complete annotations of fine-grained actions (+128% more action segments). This collection also enables evaluating the "test of time" - i.e. whether models trained on data collected in 2018 can generalise to new footage collected under the same hypotheses albeit "two years on". The dataset is aligned with 6 challenges: action recognition (full and weak supervision), action detection, action anticipation, cross-modal retrieval (from captions), as well as unsupervised domain adaptation for action recognition.

158 PAPERS • 7 BENCHMARKS

FSD50K (Freesound Database 50K)

Freesound Dataset 50k (or FSD50K for short) is an open dataset of human-labeled sound events containing 51,197 Freesound clips unequally distributed in 200 classes drawn from the AudioSet Ontology. FSD50K has been created at the Music Technology Group of Universitat Pompeu Fabra. It consists mainly of sound events produced by physical sound sources and production mechanisms, including human sounds, sounds of things, animals, natural sounds, musical instruments and more.

144 PAPERS • 2 BENCHMARKS

UrbanSound8K

Urban Sound 8K is an audio dataset that contains 8732 labeled sound excerpts (<=4s) of urban sounds from 10 classes: air_conditioner, car_horn, children_playing, dog_bark, drilling, enginge_idling, gun_shot, jackhammer, siren, and street_music. The classes are drawn from the urban sound taxonomy. All excerpts are taken from field recordings uploaded to www.freesound.org.

139 PAPERS • 3 BENCHMARKS

UCR Time Series Classification Archive
UCR Time Series Classification Archive

The UCR Time Series Archive - introduced in 2002, has become an important resource in the time series data mining community, with at least one thousand published papers making use of at least one data set from the archive. The original incarnation of the archive had sixteen data sets but since that time, it has gone through periodic expansions. The last expansion took place in the summer of 2015 when the archive grew from 45 to 85 data sets. This paper introduces and will focus on the new data expansion from 85 to 128 data sets. Beyond expanding this valuable resource, this paper offers pragmatic advice to anyone who may wish to evaluate a new algorithm on the archive. Finally, this paper makes a novel and yet actionable claim: of the hundreds of papers that show an improvement over the standard baseline (1-nearest neighbor classification), a large fraction may be misattributing the reasons for their improvement. Moreover, they may have been able to achieve the same improvement with a

40 PAPERS • 2 BENCHMARKS

CREMA-D
CREMA-D

CREMA-D is an emotional multimodal actor data set of 7,442 original clips from 91 actors. These clips were from 48 male and 43 female actors between the ages of 20 and 74 coming from a variety of races and ethnicities (African America, Asian, Caucasian, Hispanic, and Unspecified).

27 PAPERS • 7 BENCHMARKS

RAVDESS
RAVDESS (Ryerson Audio-Visual Database of Emotional Speech and Song)

The Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) contains 7,356 files (total size: 24.8 GB). The database contains 24 professional actors (12 female, 12 male), vocalizing two lexically-matched statements in a neutral North American accent. Speech includes calm, happy, sad, angry, fearful, surprise, and disgust expressions, and song contains calm, happy, sad, angry, and fearful emotions. Each expression is produced at two levels of emotional intensity (normal, strong), with an additional neutral expression. All conditions are available in three modality formats: Audio-only (16bit, 48kHz .wav), Audio-Video (720p H.264, AAC 48kHz, .mp4), and Video-only (no sound). Note, there are no song files for Actor_18.

27 PAPERS • 6 BENCHMARKS

DiCOVA
DiCOVA

The DiCOVA Challenge dataset is derived from the Coswara dataset, a crowd-sourced dataset of sound recordings from COVID-19 positive and non-COVID-19 individuals. The Coswara data is collected using a web-application2, launched in April-2020, accessible through the internet by anyone around the globe. The volunteering subjects are advised to record their respiratory sounds in a quiet environment.

20 PAPERS • 1 BENCHMARK

ICBHI Respiratory Sound Database (The Respiratory Sound database - ICBHI 2017 Challenge)

The Respiratory Sound database was originally compiled to support the scientific challenge organized at Int. Conf. on Biomedical Health Informatics - ICBHI 2017.

20 PAPERS • 2 BENCHMARKS

FSDnoisy18k

The FSDnoisy18k dataset is an open dataset containing 42.5 hours of audio across 20 sound event classes, including a small amount of manually-labeled data and a larger quantity of real-world noisy data. The audio content is taken from Freesound, and the dataset was curated using the Freesound Annotator. The noisy set of FSDnoisy18k consists of 15,813 audio clips (38.8h), and the test set consists of 947 audio clips (1.4h) with correct labels. The dataset features two main types of label noise: in-vocabulary (IV) and out-of-vocabulary (OOV). IV applies when, given an observed label that is incorrect or incomplete, the true or missing label is part of the target class set. Analogously, OOV means that the true or missing label is not covered by those 20 classes.

19 PAPERS • NO BENCHMARKS YET

SHD (Spiking Heidelberg Digits)

The Spiking Heidelberg Digits (SHD) dataset is an audio-based classification dataset of 1k spoken digits ranging from zero to nine in the English and German languages. The audio waveforms have been converted into spike trains using an artificial model of the inner ear and parts of the ascending auditory pathway. The SHD dataset has 8,156 training and 2,264 test samples. A full description of the dataset and how it was created can be found in the paper below. Please cite this paper if you make use of the dataset.

19 PAPERS • 1 BENCHMARK

VocalSound

VocalSound is a free dataset consisting of 21,024 crowdsourced recordings of laughter, sighs, coughs, throat clearing, sneezes, and sniffs from 3,365 unique subjects. The VocalSound dataset also contains meta-information such as speaker age, gender, native language, country, and health condition.

19 PAPERS • 1 BENCHMARK

EPIC-SOUNDS

EPIC-SOUNDS is a large scale dataset of audio annotations capturing temporal extents and class labels within the audio stream of the egocentric videos from EPIC-KITCHENS-100. EPIC-SOUNDS includes 78.4k categorised and 39.2k non-categorised segments of audible events and actions, distributed across 44 classes.

11 PAPERS • 2 BENCHMARKS

YouTube-100M (YouTube-100m)

The YouTube-100M data set consists of 100 million YouTube videos: 70M training videos, 10M evaluation videos, and 20M validation videos. Videos average 4.6 minutes each for a total of 5.4M training hours. Each of these videos is labeled with 1 or more topic identifiers from a set of 30,871 labels. There are an average of around 5 labels per video. The labels are assigned automatically based on a combination of metadata (title, description, comments, etc.), context, and image content for each video. The labels apply to the entire video and range from very generic (e.g. “Song”) to very specific (e.g. “Cormorant”). Being machine generated, the labels are not 100% accurate and of the 30K labels, some are clearly acoustically relevant (“Trumpet”) and others are less so (“Web Page”). Videos often bear annotations with multiple degrees of specificity. For example, videos labeled with “Trumpet” are often labeled “Entertainment” as well, although no hierarchy is enforced.

8 PAPERS • NO BENCHMARKS YET

SSC (Spiking Speech Commands v0.2)

The SSC dataset is a spiking version of the Speech Commands dataset release by Google (Speech Commands). SSC was generated using Lauscher, an artificial cochlea model. The SSC dataset consists of utterances recorded from a larger number of speakers under controlled conditions. Spikes were generated in 700 input channels, and it contains 35 word categories from a large number of speakers.

7 PAPERS • 1 BENCHMARK

VGGSound-Sparse
VGGSound-Sparse

The dataset uses VGG-Sound which consists of 10s clips collected from YouTube for 309 sound classes. A subset of ‘temporally sparse’ classes is selected using the following procedure: 5–15 videos are randomly picked from each of the 309 VGGSound classes, and manually annotated as to whether audio-visual cues are only sparsely available. As a result, 12 classes are selected (∼4 %) or 6.5k and 0.6k videos in the train and test sets, respectively. The classes include 'dog barking', 'chopping wood', 'lion roaring', 'skateboarding' etc.

5 PAPERS • NO BENCHMARKS YET

aGender

The aGender corpus contains audio recordings of predefined utterances and free speech produced by humans of different age and gender. Each utterance is labeled as one of four age groups: Child, Youth, Adult, Senior, and as one of three gender classes: Female, Male and Child.

5 PAPERS • NO BENCHMARKS YET

SONYC-UST-V2
SONYC-UST-V2

A dataset for urban sound tagging with spatiotemporal information. This dataset is aimed for the development and evaluation of machine listening systems for real-world urban noise monitoring. While datasets of urban recordings are available, this dataset provides the opportunity to investigate how spatiotemporal metadata can aid in the prediction of urban sound tags. SONYC-UST-V2 consists of 18510 audio recordings from the "Sounds of New York City" (SONYC) acoustic sensor network, including the timestamp of audio acquisition and location of the sensor.

4 PAPERS • NO BENCHMARKS YET

TAU-NIGENS Spatial Sound Events 2021
TAU-NIGENS Spatial Sound Events 2021

The TAU-NIGENS Spatial Sound Events 2021 dataset contains multiple spatial sound-scene recordings, consisting of sound events of distinct categories integrated into a variety of acoustical spaces, and from multiple source directions and distances as seen from the recording position. The spatialization of all sound events is based on filtering through real spatial room impulse responses (RIRs), captured in multiple rooms of various shapes, sizes, and acoustical absorption properties. Furthermore, each scene recording is delivered in two spatial recording formats, a microphone array one (MIC), and first-order Ambisonics one (FOA). The sound events are spatialized as either stationary sound sources in the room, or moving sound sources, in which case time-variant RIRs are used. Each sound event in the sound scene is associated with a single direction-of-arrival (DoA) if static, a trajectory DoAs if moving, and a temporal onset and offset time. The isolated sound event recordings used for t

4 PAPERS • 1 BENCHMARK

DCASE 2014
DCASE 2014

DCASE2014 is an audio classification benchmark.

3 PAPERS • NO BENCHMARKS YET

HUME-VB
HUME-VB (The Hume Vocal Bursts Dataset)

The Hume Vocal Burst Database (H-VB) includes all train, validation, and test recordings and corresponding emotion ratings for the train and validation recordings.

3 PAPERS • 7 BENCHMARKS

Chest wall lung sound dataset
Chest wall lung sound dataset

Annotated audio files (separate combined annotation file) of lung sounds as recorded from various vantage points of the chest wall. The annotation includes the sound type (Insipratory: I, Experiatory: E, Wheezes: W, Crackles: C , N:Normal), the diagnosis as decided by a specialist (Asthma, COPD, BRON, heart failure, lung fibrosis, etc.), and the location on the chest wall from which the recording was taken (Posterior: P Lower: L Left: L Right R, UPPER: U, ANTERIOR: A, MIDDLE: M). The audio file names are coded: 1. Filter type; B: BELL 20-200Hz, Diaphragm 100-500 Hz, Extended range 50-500 Hz. 2. Patient number: P1-P112.

2 PAPERS • 1 BENCHMARK

InfantMarmosetsVox

InfantMarmosetsVox is a dataset for multi-class call-type and caller identification. It contains audio recordings of different individual marmosets and their call-types. The dataset contains a total of 350 files of precisely labelled 10-minute audio recordings across all caller classes. The audio was recorded from five pairs of infant marmoset twins, each recorded individually in two separate sound-proofed recording rooms at a sampling rate of 44.1 kHz. The start and end time, call-type, and marmoset identity of each vocalization are provided, labeled by an experienced researcher. A PyTorch Dataloader is included in this dataset.

2 PAPERS • 1 BENCHMARK

SINGA:PURA
SINGA:PURA (SINGApore: Polyphonic URban Audio)

This repository contains the SINGA:PURA dataset, a strongly-labelled polyphonic urban sound dataset with spatiotemporal context. The data were collected via a number of recording units deployed across Singapore as a part of a wireless acoustic sensor network. These recordings were made as part of a project to identify and mitigate noise sources in Singapore, but also possess a wider applicability to sound event detection, classification, and localization. The taxonomy we used for the labels in this dataset has been designed to be compatible with other existing datasets for urban sound tagging while also able to capture sound events unique to the Singaporean context. Please refer to our conference paper published in APSIPA 2021 (which is found in this repository as the file "APSIPA.pdf") or download the readme ("Readme.md") for more details regarding the data collection, annotation, and processing methodologies for the creation of the dataset.

2 PAPERS • NO BENCHMARKS YET

BGG dataset (PUBG Gun Sound Dataset)

We recorded gun sounds by changing the type and position of guns to diversify distances and angles in the PUBG environment. The BGG dataset consists of 2,195 samples with 37 different types of guns and five directions, including a silence in which there is no gunfire, but noises exist. The distance from the firearms ranged from 0 meters to 600 meters. The audio was recorded in stereo (i.e., two-channel audio), and each sample contains various environmental noises (e.g., water splashing, walking, and bullet friction).

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DEEP-VOICE: DeepFake Voice Recognition (Jordan Bird)

DEEP-VOICE: Real-time Detection of AI-Generated Speech for DeepFake Voice Conversion This dataset contains examples of real human speech, and DeepFake versions of those speeches by using Retrieval-based Voice Conversion.

1 PAPER • 1 BENCHMARK

MediBeng (Synthetic Code-Switched Bengali-English Speech Conversations for Healthcare Applications)

MediBeng Dataset The MediBeng dataset contains synthetic code-switched dialogues in Bengali and English for training models in speech recognition (ASR), text-to-speech (TTS), and machine translation in clinical settings. The dataset is available under the CC-BY-4.0 license.

1 PAPER • 1 BENCHMARK

MeerKAT: Meerkat Kalahari Audio Transcripts
MeerKAT: Meerkat Kalahari Audio Transcripts

A large-scale reference dataset for bioacoustics. MeerKAT is a 1068h large-scale dataset containing data from audio-recording collars worn by free-ranging meerkats (Suricata suricatta) at the Kalahari Research Centre, South Africa, of which 184h are labeled with twelve time-resolved vocalization-type ground truth target classes, each with millisecond resolution. The labeled 184h MeerKAT subset exhibits realistic sparsity conditions for a bioacoustic dataset (96% background-noise or other signals and 4% vocalizations), dispersed across 66398 10-second samples, spanning 251562 labeled events and showcasing significant spectral and temporal variability, making it the first large-scale reference point with real-world conditions for benchmarking pretraining and finetune approaches in bioacoustics deep learning.

1 PAPER • 1 BENCHMARK

Multimodal PISA (Multimodal Piano Skills Assessment)

Dataset for multimodal skills assessment focusing on assessing piano player’s skill level. Annotations include player's skills level, and song difficulty level. Bounding box annotations around pianists' hands are also provided.

1 PAPER • 3 BENCHMARKS

PC-GITA
PC-GITA

PC-GITA is a Spanish speech corpus designed to analyze speech impairments in individuals with Parkinson's Disease (PD).

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RESPIRATORY AND DRUG ACTUATION DATASET
RESPIRATORY AND DRUG ACTUATION DATASET

Asthma is a common, usually long-term respiratory disease with negative impact on society and the economy worldwide. Treatment involves using medical devices (inhalers) that distribute medicationto the airways, and its efficiency depends on the precision of the inhalation technique. Health monitoring systems equipped with sensors and embedded with sound signal detection enable the recognition of drug actuation and could be powerful tools for reliable audio content analysis. The RDA Suite includes a set of tools for audio processing, feature extraction and classification and is provided along with a dataset consisting of respiratory and drug actuation sounds. The classification models in RDA are implemented based on conventional and advanced machine learning and deep network architectures. This study provides a comparative evaluation of the implemented approaches, examines potential improvements and discusses challenges and future tendencies. The central aim of this research is to ident

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ReefSet

The full version of ReefSet used in Williams et al. (2024). This dataset contains strongly labeled audio clips from coral reef habitats, taken across 16 unique datasets from 11 countries. This dataset can be used to test transfer learning performance of audio embedding models.

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Sound-based drone fault classification using multitask learning

arxiv : https://arxiv.org/abs/2304.11708

1 PAPER • 1 BENCHMARK

Zooniverse
Zooniverse (HumBug Zooniverse)

The Humbug Zooinverse dataset is a dataset of mosquito audio recordings. With over a thousand contributors, it contains 195,434 labels of two second duration, of which approximately 10 percent signify mosquito events.

1 PAPER • NO BENCHMARKS YET

nEMO
nEMO

Overview nEMO is a simulated dataset of emotional speech in the Polish language. The corpus contains over 3 hours of samples recorded with the participation of nine actors portraying six emotional states: anger, fear, happiness, sadness, surprise, and a neutral state. The text material used was carefully selected to represent the phonetics of the Polish language. The corpus is available for free under the Creative Commons license (CC BY-NC-SA 4.0).

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Mudestreda (Mudestreda Multimodal Device State Recognition Dataset)

Mudestreda Multimodal Device State Recognition Dataset obtained from real industrial milling device with Time Series and Image Data for Classification, Regression, Anomaly Detection, Remaining Useful Life (RUL) estimation, Signal Drift measurement, Zero Shot Flank Took Wear, and Feature Engineering purposes.

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