Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection | Paper Citation Record

Observation 2583bfab-2432-48d1-9f0c-9d3adeb9286e · outbound

This paper cites Exploring large scale pre-trained models for robust machine anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Exploring large scale pre-trained models for robust machine anomalous sound detection,

Reference 1

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Observation 24a2f040-f94e-41eb-bc2a-f820f95ac106 · outbound

This paper cites Anopatch: Towards better consistency in machine anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Anopatch: Towards better consistency in machine anomalous sound detection,

Reference 2

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Observation 590e4de5-c777-43f7-a77e-322c1f5cc935 · outbound

This paper cites Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Description and Discussion on DCASE2020 Challenge Task2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Reference 3

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Observation 63618a70-8e8a-43a9-8da0-23e98df4bdfc · outbound

This paper cites Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Description and Discussion on DCASE 2021 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring under Domain Shifted Conditions

Reference 4

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Observation daf8488f-4353-4fd8-954b-b0c19b555138 · outbound

This paper cites Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Description and Discussion on DCASE 2022 Challenge Task 2: Unsupervised Anomalous Sound Detection for Machine Condition Monitoring Applying Domain Generalization Techniques

Reference 5

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Observation ae5edfee-7d7c-42ed-833d-6bcf58d027a2 · outbound

This paper cites Description and Discussion on DCASE 2023 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Description and Discussion on DCASE 2023 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Reference 6

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Observation 24faf40e-d87e-4fe3-9942-eef240c3ba7c · outbound

This paper cites Description and Discussion on DCASE 2024 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Description and Discussion on DCASE 2024 Challenge Task 2: First-Shot Unsupervised Anomalous Sound Detection for Machine Condition Monitoring

Reference 7

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Observation 1f0e71be-0c93-45a7-bf5d-b0631f659513 · outbound

This paper cites A unifying review of deep and shallow anomaly detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection A unifying review of deep and shallow anomaly detection,

Reference 8

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Observation b4c52cdf-80e8-4a36-b37f-33f296ff35fe · outbound

This paper cites Anomalous sound detection based on interpolation deep neural network,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Anomalous sound detection based on interpolation deep neural network,

Reference 9

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Observation cb4263e3-82ed-4ad4-b0c5-2d42fe9e7bec · outbound

This paper cites Flow- based self-supervised density estimation for anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Flow- based self-supervised density estimation for anomalous sound detection,

Reference 10

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Observation 923817a6-bf60-4d92-ac1f-41424b581fc3 · outbound

This paper cites Unsupervised anomalous sound detection using self- supervised classification and group masked autoencoder for density estimation,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Unsupervised anomalous sound detection using self- supervised classification and group masked autoencoder for density estimation,

Reference 11

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Observation c0389dd2-f048-4990-a651-a7a86ed1e74f · outbound

This paper cites Unsupervised anomaly detection and localization of machine audio: A gan-based approach,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Unsupervised anomaly detection and localization of machine audio: A gan-based approach,

Reference 12

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Observation 3097c7fb-6480-4b7f-b725-cf61775f5ff0 · outbound

This paper cites Self- supervised representation learning for unsupervised anomalous sound detection under domain shift,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Self- supervised representation learning for unsupervised anomalous sound detection under domain shift,

Reference 13

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Observation bb65f0f5-718d-4a9d-97cc-e08ff8dfcf12 · outbound

This paper cites BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding

Reference 14

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Observation 995b18a4-2d47-4976-ae2b-68ece4f38635 · outbound

This paper cites SUPERB: Speech processing Universal PERformance Benchmark.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection SUPERB: Speech processing Universal PERformance Benchmark

Reference 15

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Observation 043cc9f3-8ab0-41c3-95ca-2112f182db98 · outbound

This paper cites BEATs: Audio pre-training with acoustic tokenizers,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection BEATs: Audio pre-training with acoustic tokenizers,

Reference 16

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Observation 84660058-43f4-4c49-9a60-297236e4c0f3 · outbound

This paper cites Large-scale self-supervised speech representation learning for automatic speaker verification,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Large-scale self-supervised speech representation learning for automatic speaker verification,

Reference 17

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Observation 1b1837bb-8a04-4605-a144-ffab9fbdc339 · outbound

This paper cites Attention is all you need,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Attention is all you need,

Reference 18

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Observation c2b78ae1-21e3-40b6-a8e3-443c68979cf0 · outbound

This paper cites Sub-cluster adacos: Learning representations for anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Sub-cluster adacos: Learning representations for anomalous sound detection,

Reference 19

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Observation bf5adef5-0617-490e-93aa-24e9474788e4 · outbound

This paper cites Diffusion augmentation sub-center modeling for unsupervised anomalous sound detection with partially attribute-unavailable conditions,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Diffusion augmentation sub-center modeling for unsupervised anomalous sound detection with partially attribute-unavailable conditions,

Reference 20

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Observation 7aba199b-bff7-43e7-b356-7a9bdeb22e38 · outbound

This paper cites Adaptive prototype learning for anomalous sound detection with partially known attributes,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Adaptive prototype learning for anomalous sound detection with partially known attributes,

Reference 21

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Observation 22f0fe55-78ca-4528-8ab0-332c69653e83 · outbound

This paper cites Disentangling hierarchical features for anomalous sound detection under domain shift,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Disentangling hierarchical features for anomalous sound detection under domain shift,

Reference 22

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Observation d84afced-e01e-41a1-b419-c10319fd3796 · outbound

This paper cites Joint generative-contrastive representation learning for anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Joint generative-contrastive representation learning for anomalous sound detection,

Reference 23

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Observation c77bff73-755a-4e62-beb6-0fec68dc6ffe · outbound

This paper cites Sw-wavenet: learning represen- tation from spectrogram and wavegram using wavenet for anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Sw-wavenet: learning represen- tation from spectrogram and wavegram using wavenet for anomalous sound detection,

Reference 24

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Observation 4abbe920-54f5-407d-9fc3-d97c0a9c77e5 · outbound

This paper cites Anomalous sound de- tection using self-attention-based frequency pattern analysis of machine sounds,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Anomalous sound de- tection using self-attention-based frequency pattern analysis of machine sounds,

Reference 25

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Observation 4a18d741-c2a2-4e33-bb77-e695413db075 · outbound

This paper cites Efficient algorithms for mining outliers from large data sets,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Efficient algorithms for mining outliers from large data sets,

Reference 26

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Observation d649177d-056e-406d-9f0e-9a53647833e0 · outbound

This paper cites Lof: identifying density-based local outliers,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Lof: identifying density-based local outliers,

Reference 27

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Observation fe235337-9d6a-4fac-9f77-0721fd43fce3 · outbound

This paper cites Deep autoencoding gaussian mixture model for unsupervised anomaly detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Deep autoencoding gaussian mixture model for unsupervised anomaly detection,

Reference 28

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Observation c60043e0-e2fc-463d-bb12-953aa7299f35 · outbound

This paper cites wav2vec 2.0: A framework for self-supervised learning of speech representations,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection wav2vec 2.0: A framework for self-supervised learning of speech representations,

Reference 29

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Observation b2b34c29-9d64-4b5f-b84e-92db90c26761 · outbound

This paper cites Hubert: Self-supervised speech representation learning by masked prediction of hidden units,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Hubert: Self-supervised speech representation learning by masked prediction of hidden units,

Reference 30

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Observation b96af966-1ae9-4e06-a213-a42cf3af17a2 · outbound

This paper cites Unispeech: Unified speech representation learning with labeled and unlabeled data,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Unispeech: Unified speech representation learning with labeled and unlabeled data,

Reference 31

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Observation b8482b24-8f69-4fc0-8742-0862cca6d9b9 · outbound

This paper cites Wavlm: Large-scale self-supervised pre- training for full stack speech processing,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Wavlm: Large-scale self-supervised pre- training for full stack speech processing,

Reference 32

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Observation 57654bdf-5062-4444-9bfd-d7127e75fc66 · outbound

This paper cites AST: Audio Spectrogram Trans- former,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection AST: Audio Spectrogram Trans- former,

Reference 33

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Observation e6245541-fb47-4510-9082-2d06f367d5ca · outbound

This paper cites An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection An Image is Worth 16x16 Words: Transformers for Image Recognition at Scale

Reference 34

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Observation 709701f0-714b-4389-8aa7-d314a822cc51 · outbound

This paper cites Imagebind: One embedding space to bind them all,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Imagebind: One embedding space to bind them all,

Reference 35

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Observation 5633461f-9dbe-4273-8c0a-43855b68585e · outbound

This paper cites Self-supervised audio teacher-student transformer for both clip-level and frame-level tasks,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Self-supervised audio teacher-student transformer for both clip-level and frame-level tasks,

Reference 36

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Observation 07a9346d-c2d2-4a23-8987-7b6918b937c0 · outbound

This paper cites Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Emotion Recognition from Speech Using Wav2vec 2.0 Embeddings

Reference 37

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Observation 7eb24b15-dd8d-4afb-a605-f5e0cfcafd38 · outbound

This paper cites Sparsely shared lora on whisper for child speech recognition,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Sparsely shared lora on whisper for child speech recognition,

Reference 38

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Observation 96de8892-18ad-45a7-9f53-d58fe1e5c7a6 · outbound

This paper cites Prefix-Tuning: Optimizing Continuous Prompts for Generation.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Prefix-Tuning: Optimizing Continuous Prompts for Generation

Reference 39

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Observation 230c6289-10b6-4d58-8cd3-04ab2f082718 · outbound

This paper cites Efficient adapter transfer of self- supervised speech models for automatic speech recognition,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Efficient adapter transfer of self- supervised speech models for automatic speech recognition,

Reference 40

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Observation 0ab6f231-1a2b-489e-8746-a24cd0a5138f · outbound

This paper cites Librispeech: an asr corpus based on public domain audio books,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Librispeech: an asr corpus based on public domain audio books,

Reference 41

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Observation 8e9b6435-fdda-4759-8b75-0826788451cd · outbound

This paper cites Audio set: An ontology and human- labeled dataset for audio events,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Audio set: An ontology and human- labeled dataset for audio events,

Reference 42

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Observation db2ae0d5-0428-4ca6-a69c-49aa9acf0cd1 · outbound

This paper cites Attentive Statistics Pooling for Deep Speaker Embedding.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Attentive Statistics Pooling for Deep Speaker Embedding

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Observation 1b4674ad-e146-4642-b820-44d069e6c61a · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection LoRA: Low-Rank Adaptation of Large Language Models

Reference 44

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Observation 54d2b093-ce74-4e83-a504-93d0c3cf1ec6 · outbound

This paper cites Robust anomaly sound detection framework for machine condition monitoring,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Robust anomaly sound detection framework for machine condition monitoring,

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Observation 0b6e2468-798d-4d43-a926-88787a608997 · outbound

This paper cites Arcface: Additive angular margin loss for deep face recognition,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Arcface: Additive angular margin loss for deep face recognition,

Reference 46

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Observation d81d3bbe-16fd-46fe-816c-a2afe504b993 · outbound

This paper cites Large margin softmax loss for speaker verification,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Large margin softmax loss for speaker verification,

Reference 47

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Observation b265083a-88d1-4d99-9653-5be96eee53ad · outbound

This paper cites Why do angular margin losses work well for semi-supervised anomalous sound detection?.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Why do angular margin losses work well for semi-supervised anomalous sound detection?

Reference 48

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Observation f07e1d24-d889-4255-9523-a0151a5ef706 · outbound

This paper cites Toyadmos: A dataset of miniature-machine operating sounds for anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Toyadmos: A dataset of miniature-machine operating sounds for anomalous sound detection,

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Observation 4b10770a-d643-4ece-8b04-dab4ed25440a · outbound

This paper cites ToyADMOS2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection ToyADMOS2: Another dataset of miniature-machine operating sounds for anomalous sound detection under domain shift conditions

Reference 50

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Observation 952fa822-c9d1-4ee6-b876-2a342b90c44a · outbound

This paper cites MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection MIMII Dataset: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection

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Observation 4cd02071-a519-4581-9e97-cb3e180980d8 · outbound

This paper cites MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization Task.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection MIMII DG: Sound Dataset for Malfunctioning Industrial Machine Investigation and Inspection for Domain Generalization Task

Reference 52

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Observation 59f51c75-90af-4ba6-9b5f-a9a486078662 · outbound

This paper cites Imad-ds: A dataset for industrial multi-sensor anomaly detection under domain shift conditions,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Imad-ds: A dataset for industrial multi-sensor anomaly detection under domain shift conditions,

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Observation 39b5dc21-4681-4402-a80b-e964109fe5bd · outbound

This paper cites Mobilefacenets: Efficient cnns for accurate real-time face verification on mobile devices,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Mobilefacenets: Efficient cnns for accurate real-time face verification on mobile devices,

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Observation 58491898-c455-475f-8a22-1c8e643c467f · outbound

This paper cites Ensemble of complemen- tary anomaly detectors under domain shifted conditions,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Ensemble of complemen- tary anomaly detectors under domain shifted conditions,

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Observation 7799173e-f18a-47a1-a721-77138087f753 · outbound

This paper cites First- shot anomaly sound detection for machine condition monitoring: A do- main generalization baseline,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection First- shot anomaly sound detection for machine condition monitoring: A do- main generalization baseline,

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Observation b3d250d0-0b3d-4223-b724-39b0c66c2f73 · outbound

This paper cites Specaugment: A simple data augmentation method for automatic speech recognition,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Specaugment: A simple data augmentation method for automatic speech recognition,

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Observation c3bcac35-010c-413f-b864-8d328e19c33e · outbound

This paper cites Anomalous sound detection using cnn-based features by self supervised learning,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Anomalous sound detection using cnn-based features by self supervised learning,

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Observation 0517ded9-3dc0-4632-9ee9-b43c8fd4fda0 · outbound

This paper cites Ced: Consistent ensemble distillation for audio tagging,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Ced: Consistent ensemble distillation for audio tagging,

Reference 59

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Observation 0eaa8651-0196-42e0-a593-6924472d3a41 · outbound

This paper cites Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation,

Reference 60

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Observation 01852839-fff2-4b92-be06-5aca0a6f8561 · outbound

This paper cites Anomalous sound detection using spectral-temporal information fusion,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Anomalous sound detection using spectral-temporal information fusion,

Reference 61

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Observation ba9fe2d5-3e0f-486d-b8c2-8cb67021d06c · outbound

This paper cites An effective anomalous sound detection method based on represen- tation learning with simulated anomalies,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection An effective anomalous sound detection method based on represen- tation learning with simulated anomalies,

Reference 62

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This paper cites Time- weighted frequency domain audio representation with gmm estimator for anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Time- weighted frequency domain audio representation with gmm estimator for anomalous sound detection,

Reference 63

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Observation 3606762b-caf2-45c0-9366-b7ac0b73d6fc · outbound

This paper cites Anomalous sound detection based on self-supervised learning,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Anomalous sound detection based on self-supervised learning,

Reference 64

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This paper cites Self-Supervised Learning for Anomalous Sound Detection.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Self-Supervised Learning for Anomalous Sound Detection

Reference 65

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Observation c3608259-8475-482d-8234-aa0e8c7cac90 · outbound

This paper cites Stream-based active learning for anomalous sound detection in machine condition monitoring,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Stream-based active learning for anomalous sound detection in machine condition monitoring,

Reference 66

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Observation c1842064-af88-46b8-a5b2-0b1a7d11e03e · outbound

This paper cites A dual-path frame- work with frequency-and-time excited network for anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection A dual-path frame- work with frequency-and-time excited network for anomalous sound detection,

Reference 67

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Observation 7326557b-7d8c-4182-a510-8fe20ffe6935 · outbound

This paper cites Aithu system for first-shot unsupervised anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Aithu system for first-shot unsupervised anomalous sound detection,

Reference 68

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Observation 78cc8826-6df9-41f3-8753-56a1eae2a4e4 · outbound

This paper cites Thuee system for first-shot unsupervised anomalous sound detection,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Thuee system for first-shot unsupervised anomalous sound detection,

Reference 69

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Observation f4eca228-3356-4df1-8584-882900056c9f · outbound

This paper cites Enhanced unsupervised anomalous sound detection using conditional autoencoder for machine condition monitoring,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Enhanced unsupervised anomalous sound detection using conditional autoencoder for machine condition monitoring,

Reference 70

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Observation 2867e482-aced-4b14-814b-ddd539f19333 · outbound

This paper cites Smote: synthetic minority over-sampling technique,.

Exploring Self-Supervised Audio Models for Generalized Anomalous Sound Detection Smote: synthetic minority over-sampling technique,

Reference 71

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