陳羿豐 Yi-Feng Chen
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# 正在看的論文/文章/程式 ## 正在重現 1. Landmark-based audio fingerprinting https://github.com/dpwe/audfprint 2. Dejavu https://github.com/worldveil/dejavu 3. Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrasive Learning https://arxiv.org/abs/2010.11910 ## 資訊領域 2021/9/3 - Illegal Audio Copy Detection using Fundamental Frequency Map 2021/9/2 - 孙甲松, 张菁芸, 杨毅. 基于子带频谱质心特征的高效音频指纹检索 2021/8/29 - 以地標為特徵之音訊指紋系統的改進 顏琬庭 2021/7/8 - Supervised Contrastive Learning 2021/6/20 - Playing Atari with Deep Reinforcement Learning 2021/6/15 - Asymptotic Distribution of Coordinates on High Dimensional Spheres 2021/6/11 - When Does Contrastive Visual Representation Learning Work? https://arxiv.org/pdf/2105.05837.pdf 2021/6/9 - Adversarial Attacks on Audio Source Separation - MTG-Jamendo dataset - A DIRT-T Approach to Unsupervised Domain Adaptation - Virtual Adversarial Training: A Regularization Method for Supervised and Semi-Supervised Learning 2021/6/8 - Semi-supervised Domain Adaptation via Minimax Entropy 2021/6/7 - Learning Noise-Invariant Representations for Robust Speech Recognition 2021/6/4 - Sublinear Maximum Inner Product Search using Concomitants of Extreme Order Statistic https://arxiv.org/pdf/2012.11098.pdf 2021/6/2 - Panako 2021/6/1 - Unsupervised Deep Learning Recurrent Model for Audio Fingerprinting 2021/5/19 - GPU-accelerated Hungarian algorithms for the Linear Assignment Problem 2021/5/14 - BPR: Bayesian Personalized Ranking from Implicit Feedback 2021/4/30 - A Binary Auditory Words Model for Audio Content Identification 2021/4/28 - A Style-Based Generator Architecture for Generative Adversarial Networks https://arxiv.org/abs/1812.04948 - Analyzing and Improving the Image Quality of StyleGAN https://arxiv.org/abs/1912.04958 2021/4/27 - Wasserstein GAN https://arxiv.org/abs/1701.07875 2021/4/21 - A spectrogram-based audio fingerprinting system for content-based copy detection - SURVEY AND EVALUATION OF AUDIO FINGERPRINTING SCHEMES FOR MOBILE QUERY-BY-EXAMPLE APPLICATIONS - CRIMS CONTENT-BASED COPY DETECTION SYSTEM FOR TREVCID 2021/4/15 - Self-Attention with Relative Position Representations https://arxiv.org/pdf/1803.02155.pdf 2021/4/14 - Self-training with Noisy Student improves ImageNet classification https://arxiv.org/pdf/1911.04252.pdf - Conformer: Convolution-augmented Transformer for Speech Recognition https://arxiv.org/pdf/2005.08100.pdf - 改進以地標為基礎的音訊指紋辨識 - 基於 GPU 加速之巨量音訊指紋系統 - 使用排序學習演算法產生重新排名以改進的音訊指紋辨識 - Additive Margin Softmax for Face Verification https://arxiv.org/pdf/1801.05599.pdf 2021/4/13 - Very Deep Convolutional Networks for Large-Scale Image Recognition https://arxiv.org/abs/1409.1556 - A Close Look at Deep Learning with Small Data https://arxiv.org/pdf/2003.12843.pdf 2021/4/8 - MixMatch: A Holistic Approach to Semi-Supervised Learning https://arxiv.org/abs/1905.02249 2021/3/30 - Contrastive Learning of General-Purpose Audio Representations https://arxiv.org/abs/2010.10915 - 可惜沒有音訊指紋 2021/3/25 - Noise removal of audio clips for fingerprint matching - Robust Audio Fingerprinting Method Using Prominent Peak Pair Based on Modulated Complex Lapped Transform - 藉由目標區域以及雜湊表調整對以地標為特徵音訊指紋的改進。廖信富 2021/3/9 - A Case for Reproducibility in MIR: Replication of ‘A Highly Robust Audio Fingerprinting System’ https://transactions.ismir.net/articles/10.5334/tismir.4/ 2021/3/2 - MASK: Robust Local Features for Audio Fingerprinting 2021/2/22 - A Highly Robust Audio Fingerprinting System ISMIR 2002 2021/2/17 - Audio Feature Extraction for Fingerprinting & Similarity Search. Vlad Limbean - 以雙向檢索及排序學習演算法來改進音訊指紋辨識。唐子翔 2021/2/8 - NUS-48E Sung and Spoken Lyrics Corpus https://smcnus.comp.nus.edu.sg/nus-48e-sung-and-spoken-lyrics-corpus/ 2021/2/5 - WHAM! and WHAMR! The WSJ0 Hipster Ambient Mixtures dataset http://wham.whisper.ai/ 2021/2/4 - Deep Learning for the Precise Peak Detection in High-Resolution LC−MS Data - Robust Audio Fingerprinting Method Using Prominent Peak Pair Based on Modulated Complex Lapped Transform 2021/1/29 - Query Adaptive Similarity for Large Scale Object Retrieval - Single-Agent Optimization Through Policy Iteration Using Monte-Carlo Tree Search 2021/1/27 - CONTRASTIVE UNSUPERVISED LEARNING FOR AUDIO FINGERPRINTING https://arxiv.org/abs/2010.13540 用VGG和ResNet,degradation有pitch、tempo、speed - VoxCeleb dataset - Momentum Contrast for Unsupervised Visual Representation Learning 2021/1/26 - Vectorized Benchmarks for the Berkeley Dwarfs - Attacking SameGame using Monte-Carlo Tree Search 2021/1/22 - An Empirical Survey of Data Augmentation for Time Series Classification with Neural Networks - Data augmentation and loss normalization for deep noise suppression https://arxiv.org/abs/2008.06412 2021/1/21 - A Simple Framework for Contrastive Learning of Visual Representations https://arxiv.org/abs/2002.05709 2021/1/20 - https://github.com/facebookresearch/faiss/wiki/Faiss-code-structure - https://github.com/facebookresearch/faiss/issues/1578 2021/1/8 - Time Stretching & Pitch Shifting with the Web Audio API: Where are we at? 2021/1/5 - Pruning Subsequence Search with Attention-Based Embedding - Speeding up audio fingerprinting over GPUs 2020/12/26 - Henry Z. Lo. and Cohen, Joseph Paul “Academic Torrents: Scalable Data Distribution.” Neural Information Processing Systems Challenges in Machine Learning (CiML) Workshop, 2016, http://arxiv.org/abs/1603.04395. 2020/12/22 - SpecAugment: A Simple Data Augmentation Method for Automatic Speech Recognition https://arxiv.org/abs/1904.08779 2020/12/17 - Billion-scale similarity search with GPUs https://arxiv.org/abs/1702.08734 2020/12/8 - SPICE: Self-supervised Pitch Estimation https://arxiv.org/abs/1910.11664 2020/12/1 - https://github.com/pytorch/audio/issues/800 2020/11/30 - An Analysis of the Effect of Data Augmentation Methods: Experiments for a Musical Genre Classification Task https://transactions.ismir.net/articles/10.5334/tismir.26/ - AudioSet dataset https://research.google.com/audioset/ - FSD50K dataset https://zenodo.org/record/4060432#.X9r_bhZ-VPY - Aachen Impulse Response Database https://www.iks.rwth-aachen.de/en/research/tools-downloads/databases/aachen-impulse-response-database/ 2020/11/27 - Layer normalization https://arxiv.org/abs/1607.06450 2020/11/25 - Efficient SIMD Implementation for Accelerating Convolutional Neural Network - https://github.com/baziotis/2D-Image-Convolution-MPI-SIMD 2020/11/23 - FMA dataset https://github.com/mdeff/fma 2020/11/20 - Query by Singing and Humming http://disp.ee.ntu.edu.tw/tutorial/Query-By-Singing-and-Hummimg.pdf - Query by Singing/Humming System Based on Deep Learning https://www.ripublication.com/ijaer17/ijaerv12n13_26.pdf - Neural Audio Fingerprint for High-specific Audio Retrieval based on Contrasive Learning https://arxiv.org/abs/2010.11910 - MUSAN dataset http://www.openslr.org/17/ 2020/11/18 - Now Playing: Continuous low-power music recognition https://arxiv.org/abs/1711.10958 - Simultaneous feature learning and hash coding with deep neural networks https://arxiv.org/abs/1504.03410 - Follow That Tune – Adaptive Approach to DTW-based Query-by-Humming System http://ics.p.lodz.pl/~basta/pre-prints/Stasiak_AoA_2014.pdf - DALI dataset 2020/11/17 - THE IMPORTANCE OF F0 TRACKING INQUERY-BY-SINGING-HUMMING http://www.terasoft.com.tw/conf/ismir2014/proceedings/T051_147_Paper.pdf 2020/11/13 - A Matrix Learning Reality Check https://arxiv.org/abs/2003.08505 2020/11/11 - SAMAF: Sequence-to-sequence Autoencoder Model for Audio Fingerprinting 2020/11/7 - https://en.m.wikipedia.org/wiki/External_sorting 2020/11/5 - Dejavu https://github.com/worldveil/dejavu - A fast algorithm for local minimum and maximum filters on rectangular and octagonal kernels https://www.sciencedirect.com/science/article/pii/016786559290069C - Frank Kurth, Meinard Müller. Efficient Index-Based Audio Matching, 2008. http://dx.doi.org/10.1109/TASL.2007.911552 2020/9/21 - COMPARATIVE ANALYSIS BETWEEN AUDIO FINGERPRINTING ALGORITHMS 2020/6/19 - An Industrial-Strength Audio Search Algorithm ## 這不是資訊領域 11/1 http://www.psikofarmakoloji.org/pdf/22_3_12.pdf https://www.reddit.com/r/singing/comments/96pp6w/any_singer_with_adhd_meds_and_singing_got_a_few/ Mascii 2.0 ```abc T:野(ㄗㄨㄛ`)玫(一ㄝˋ)瑰(ㄏㄠˇㄋㄢˊ) E2E2E2E2 | (GF)(FE)D4 | D2D2E2F2 | G4c4 w:老 師 出 了 個 _ 作 _ 業 很 難 寫 的 作 業 E2E2E2E2 | (G^F)(FE)D4 | G2G2A3G | (^FG)(AB)G4 w:清 早 出 來 真 _ 陰 _ 險 急 忙 跑 去 近 _ 前 _ 看 (GB)(AG) (^FE)(^DE) | c3^F!fermata!G4 | D2D2E2F2 | G2(AB)+fermata+c4 w: 越 _ 看 _ 越 _ 覺 _ 寫 不 完 作 業 作 業 好 難 _ 寫 A2c2F2A2 | C2(ED)C4 |] w:我 大 概 要 被 當 _ 了 ```

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