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ArXiv Papers Related to Computer Science, AI, Deep Learning, Computer Vision, NLP, etc

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πŸ—’ Learning Transposition-Invariant Interval Features from Symbolic Music and Audio
πŸ‘₯ Stefan Lattner, Maarten Grachten, Gerhard Widmer
πŸ“— PDF


πŸ—’ Towards Automated Single Channel Source Separation using Neural Networks
πŸ‘₯ Arpita Gang, Pravesh Biyani, Akshay Soni
πŸ“— PDF


πŸ—’ Synthesizing Diverse, High-Quality Audio Textures
πŸ‘₯ Joseph Antognini, Matt Hoffman, Ron J. Weiss
πŸ“— PDF


πŸ—’ Quaternion Convolutional Neural Networks for End-to-End Automatic Speech Recognition
πŸ‘₯ Titouan Parcollet, Ying Zhang, Mohamed Morchid, Chiheb Trabelsi, Georges LinarΓ¨s, Renato De Mori, Yoshua Bengio
πŸ“— PDF


πŸ—’ A Simple Fusion of Deep and Shallow Learning for Acoustic Scene Classification
πŸ‘₯ Eduardo Fonseca, Rong Gong, Xavier Serra
πŸ“— PDF


πŸ—’ Speaker Adapted Beamforming for Multi-Channel Automatic Speech Recognition
πŸ‘₯ Tobias Menne, Ralf SchlΓΌter, Hermann Ney
πŸ“— PDF


πŸ—’ End-to-End Speech Recognition From the Raw Waveform
πŸ‘₯ Neil Zeghidour, Nicolas Usunier, Gabriel Synnaeve, Ronan Collobert, Emmanuel Dupoux
πŸ“— PDF


πŸ—’ Frequency domain variants of velvet noise and their application to speech processing and synthesis: with appendices
πŸ‘₯ Hideki Kawahara, Ken-Ichi Sakakibara, Masanori Morise, Hideki Banno, Tomoki Toda, Toshio Irino
πŸ“— PDF


πŸ—’ A Weighted Superposition of Functional Contours Model for Modelling Contextual Prominence of Elementary Prosodic Contours
πŸ‘₯ Branislav Gerazov, GΓ©rard Bailly, Yi Xu
πŸ“— PDF


πŸ—’ Towards an efficient deep learning model for musical onset detection
πŸ‘₯ Rong Gong, Xavier Serra
πŸ“— PDF


πŸ—’ Towards multi-instrument drum transcription
πŸ‘₯ Richard Vogl, Gerhard Widmer, Peter Knees
πŸ“— PDF


πŸ—’ Cover Song Synthesis by Analogy
πŸ‘₯ Christopher J. Tralie
πŸ“— PDF


πŸ—’ Extending Recurrent Neural Aligner for Streaming End-to-End Speech Recognition in Mandarin
πŸ‘₯ Linhao Dong, Shiyu Zhou, Wei Chen, Bo Xu
πŸ“— PDF


πŸ—’ A 5-Dimensional Tonnetz for Nearly Symmetric Hexachords
πŸ‘₯ Vaibhav Mohanty
πŸ“— PDF


πŸ—’ Monaural source enhancement maximizing source-to-distortion ratio via automatic differentiation
πŸ‘₯ Hiroaki Nakajima, Yu Takahashi, Kazunobu Kondo, Yuji Hisaminato
πŸ“— PDF


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πŸ—’ Text-Independent Speaker Verification Based on Deep Neural Networks and Segmental Dynamic Time Warping
πŸ‘₯ Mohamed Adel, Mohamed Afify, Akram Gaballah
πŸ“— PDF


πŸ—’ Conditioning Deep Generative Raw Audio Models for Structured Automatic Music
πŸ‘₯ Rachel Manzelli, Vijay Thakkar, Ali Siahkamari, Brian Kulis
πŸ“— PDF


πŸ—’ Frame-level Instrument Recognition by Timbre and Pitch
πŸ‘₯ Yun-Ning Hung, Yi-Hsuan Yang
πŸ“— PDF


πŸ—’ Sounderfeit: Cloning a Physical Model using a Conditional Adversarial Autoencoder
πŸ‘₯ Stephen Sinclair
πŸ“— PDF


πŸ—’ Convolutional Neural Networks to Enhance Coded Speech
πŸ‘₯ Ziyue Zhao, Huijun Liu, Tim Fingscheidt
πŸ“— PDF


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πŸ—’ Weakly Supervised Deep Recurrent Neural Networks for Basic Dance Step Generation
πŸ‘₯ Nelson Yalta, Shinji Watanabe, Kazuhiro Nakadai, Tetsuya Ogata
πŸ“— PDF


πŸ—’ Evaluating the Effects of Material Sonification in Tactile Devices
πŸ‘₯ Rodrigo MartΓ­n, Michael Weinmann, Matthias B. Hullin
πŸ“— PDF


πŸ—’ A Computational Study of the Role of Tonal Tension in Expressive Piano Performance
πŸ‘₯ Carlos Cancino-ChacΓ³n, Maarten Grachten
πŸ“— PDF


πŸ—’ Exploring End-to-End Techniques for Low-Resource Speech Recognition
πŸ‘₯ Vladimir Bataev, Maxim Korenevsky, Ivan Medennikov, Alexander Zatvornitskiy
πŸ“— PDF


πŸ—’ An energy-based generative sequence model for testing sensory theories of Western harmony
πŸ‘₯ Peter M. C. Harrison, Marcus T. Pearce
πŸ“— PDF


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πŸ—’ Phase reconstruction from amplitude spectrograms based on von-Mises-distribution deep neural network
πŸ‘₯ Shinnosuke Takamichi, Yuki Saito, Norihiro Takamune, Daichi Kitamura, Hiroshi Saruwatari
πŸ“— PDF


πŸ—’ Interpreting and Explaining Deep Neural Networks for Classification of Audio Signals
πŸ‘₯ SΓΆren Becker, Marcel Ackermann, Sebastian Lapuschkin, Klaus-Robert MΓΌller, Wojciech Samek
πŸ“— PDF


πŸ—’ On Training Recurrent Networks with Truncated Backpropagation Through Time in Speech Recognition
πŸ‘₯ Hao Tang, James Glass
πŸ“— PDF


πŸ—’ Foreign English Accent Adjustment by Learning Phonetic Patterns
πŸ‘₯ Fedor Kitashov, Elizaveta Svitanko, Debojyoti Dutta
πŸ“— PDF


πŸ—’ Approximate k-space models and Deep Learning for fast photoacoustic reconstruction
πŸ‘₯ Andreas Hauptmann, Ben Cox, Felix Lucka, Nam Huynh, Marta Betcke, Paul Beard, Simon Arridge
πŸ“— PDF


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πŸ“— Sound
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πŸ—’ Auto-adaptive Resonance Equalization using Dilated Residual Networks
πŸ‘₯ Maarten Grachten, Emmanuel Deruty, Alexandre Tanguy
πŸ“— PDF


πŸ—’ Unified Hypersphere Embedding for Speaker Recognition
πŸ‘₯ Mahdi Hajibabaei, Dengxin Dai
πŸ“— PDF


πŸ—’ Multi-scale Alignment and Contextual History for Attention Mechanism in Sequence-to-sequence Model
πŸ‘₯ Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
πŸ“— PDF


πŸ—’ Phonetic-and-Semantic Embedding of Spoken Words with Applications in Spoken Content Retrieval
πŸ‘₯ Yi-Chen Chen, Sung-Feng Huang, Chia-Hao Shen, Hung-yi Lee, Lin-shan Lee
πŸ“— PDF


πŸ—’ A Fully Convolutional Neural Network Approach to End-to-End Speech Enhancement
πŸ‘₯ Frank Longueira, Sam Keene
πŸ“— PDF


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πŸ“— Computational Complexity
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πŸ—’ Referenceless Performance Evaluation of Audio Source Separation using Deep Neural Networks
πŸ‘₯ Emad M. Grais, Hagen Wierstorf, Dominic Ward, Russell Mason, Mark D. Plumbley
πŸ“— PDF


πŸ—’ Truly unsupervised acoustic word embeddings using weak top-down constraints in encoder-decoder models
πŸ‘₯ Herman Kamper
πŸ“— PDF


πŸ—’ End-to-end Models with auditory attention in Multi-channel Keyword Spotting
πŸ‘₯ Haitong Zhang, Junbo Zhang, Yujun Wang
πŸ“— PDF


πŸ—’ Sequence-to-sequence Models for Small-Footprint Keyword Spotting
πŸ‘₯ Haitong Zhang, Junbo Zhang, Yujun Wang
πŸ“— PDF


πŸ—’ Deep Learning for Tube Amplifier Emulation
πŸ‘₯ Eero-Pekka DamskΓ€gg, Lauri Juvela, Etienne Thuillier, Vesa VΓ€limΓ€ki
πŸ“— PDF


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πŸ“— Artificial Intelligence
πŸ‘‰ #ArtificialIntelligence πŸ‘ˆ

πŸ“— Hardware Architecture
πŸ‘‰ #HardwareArchitecture πŸ‘ˆ

πŸ“— Computational Complexity
πŸ‘‰ #ComputationalComplexity πŸ‘ˆ

πŸ“— Computational Engineering, Finance, and Science
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