2022

Conferences and Workshops

• YM2413-MDB : A Multi-Instrumental FM Video Game Music Dataset with Emotion Annotations
  Eunjin Choi, Yoonjin Chung, Seolhee Lee, Jong Ik Jeon, Taegyun Kwon, and Juhan Nam
  Proceedings of the 23nd International Society for Music Information Retrieval Conference (ISMIR), 2022 [paper] [website]
• Analysis and Detection of Singing Techniques in Repertoires of J-POP Solo Singers
  Yuya Yamamoto, Juhan Nam, and Hiroko Terasawa
  Proceedings of the 23nd International Society for Music Information Retrieval Conference (ISMIR), 2022 [paper]
• Neural Vocoder Feature Estimation for Dry Singing Voice Separation
  Jaekwon Im, Soonbeom Choi, Sangeon Yong, Juhan Nam
  Proceedings of the 14th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2022
• Temporal Feedback Convolutional Recurrent Neural Networks for Speech Command Recognition
  Taejun Kim, Juhan Nam
  Proceedings of the 14th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2022 [paper]
• Hi, KIA: A Speech Emotion Recognition Dataset for Wake-Up Words
  Taesu Kim, SeungHeon Doh, Gyunpyo Lee, Hyung seok Jun, Juhan Nam, and Hyeon-Jeong Suk
  Proceedings of the 14th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2022 [paper]
• Seung-ee and Kkaebi: A VR-Mobile Cross Platform Game based on Co-Presence for a Balanced Immersive Experience
  Jinwook Kim, Pooseung Koh, Seokjun Kang, Hyunyoung Jang, Juhan Nam, Young Yim Doh, and Jeongmi Lee
  Proceedings of the Annual Symposium on Computer-Human Interaction in Play, Extended Abstract (Student Game Competition), 2022 [paper] [video]
  *** Audience Choice Award ***
• Joint Estimation of Fader and Equalizer Gains of DJ Mixers using Convex Optimization
  Taejun Kim, Yi-Hsuan Yang, and Juhan Nam
  Proceedings of the International Conference on Digital Audio Effects (DAFx), 2022 [paper]
• Deformable CNN and Imbalance-Aware Feature Learning for Singing Technique Classification
  Yuya Yamamoto, Juhan Nam, and Hiroko Terasawa
  Proceedings of the 23rd INTERSPEECH Conference (Interspeech), 2022 [paper]
• The Melody of the Mysterious Stones: A VR Mindfulness Game Using Sound Spatialization
  Haven Kim, Jaeran Choi, Young Yim Doh, and Juhan Nam
  Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Extended Abstract (Student Game Competition), 2022 [pdf] [video]
• Classy Trash Monster: An Educational Game for Teaching Machine Learning to Non-major Students
  Joonhyung Bae, Karam Eum, Haram Kwon, Seolhee Lee, Juhan Nam, and Young Yim Doh
  Proceedings of the ACM CHI Conference on Human Factors in Computing Systems, Extended Abstract (Student Game Competition), 2022 [pdf] [video]
  *** Winner of Student Game Competition in the Category of Transformative and Transgressive Play ***
• Pseudo-Label Transfer from Frame-Level to Note-Level in a Teacher-Student Framework for Singing Transcription from Polyphonic Music
  Sangeun Kum, Jongpil Lee, Keunhyoung Luke Kim, Taehyoung Kim, and Juhan Nam
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 [paper]
• A Melody-Unsupervision Model for Singing Voice Synthesis
  Soonbeom Choi and Juhan Nam
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2022 [paper] [website]

2021

Journals

• Quantitative Analysis of Piano Performance Proficiency Focusing on Difference Between Hands
  Sarah Kim, Jeong Mi Park, Seungyeon Rhyu, Juhan Nam, Kyogu Lee
  PLOS ONE, 2021 [paper]
• Special Issue on Deep Learning for Applications in Acoustics: Modeling, Synthesis, and Listening (Editorial)
  Leonardo Gabrielli, György Fazekas, and Juhan Nam
  Applied Sciences, 2021 [paper]

Conferences and Workshops

• Investigating Time-Frequency Representations for Audio Feature Extraction in Singing Technique Classification
  Yuya Yamamoto, Juhan Nam, Hiroko Terasawa, and Yuzuru Hiraga
  Proceedings of the 13th Asia Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA), 2021 [paper]
• Million Song Search: Web Interface for Semantic Music Search Using Musical Word Embedding
  SeungHeon Doh, Jongpil Lee, and Juhan Nam
  Late Breaking Demo in the 22st International Society for Music Information Retrieval Conference (ISMIR), 2021 [paper]
• Music Playlist Title Generation: A Machine-Translation Approach
  Seungheon Doh, Junwon Lee, and Juhan Nam
  Proceedings of the 2nd Workshop on NLP for Music and Spoken Audio (NLP4MuSA), 2021 [paper] [video]
• Learning a Cross-Domain Embedding Space of Vocal and Mixed audio with a Structure-Preserving Triplet Loss
  Keunhyoung Kim, Jongpil Lee, Sangeun Kum, and Juhan Nam
  Proceedings of the 22nd International Society for Music Information Retrieval Conference (ISMIR), 2021 [paper] [website]
• EMOPIA: A Multi-Modal Pop Piano Dataset For Emotion Recognition and Emotion-based Music Generation
  Hsiao-Tzu Hung, Joann Ching, Seungheon Doh, Nabin Kim, Juhan Nam, and Yi-Hsuan Yang
  Proceedings of the 22nd International Society for Music Information Retrieval Conference (ISMIR), 2021 [paper] [dataset]
• Mixed Scape: Development of Framework and Artwork for Auditory Correspondence in Mixed Reality
  Seungsoon Park, Jongpil Lee, Taewan Kim, Tae Hong Park, Joonhyung Bae, and Juhan Nam
  Proceedings of International Computer Music Conference (ICMC), 2021 [paper] [artwork]
• Emotion Classification and Analysis of Expressive Performances in Classical Piano Music
  Yoojin Kim, Jeongmi Park, Dasaem Jeong, Taegyun Kwon, Jonghwa Park, and Juhan Nam
  Proceedings of the 16th International Conference on Music Perception and Cognition (ICMPC16), 2021
• Communication of Emotion Modified by the Performer in Classical Piano Pieces
  Ju-Sung Ham, Youjeong Hong, Jeongmi Park, Jonghwa Park, Juhan Nam, and Kyogu Lee
  Proceedings of the 16th International Conference on Music Perception and Cognition (ICMPC16), 2021
• Correlation Analysis Between Both Hands and Musical Score for Quantitative Evaluation of Piano Performance
  Sarah Kim, Seungyeon Rhyu, Juhan Nam, and Kyogu Lee
  Proceedings of the 16th International Conference on Music Perception and Cognition (ICMPC16), 2021
• Reverse-Engineering The Transition Regions of Real-World DJ Mixes using Sub-band Analysis with Convex Optimization
  Taejun Kim, Yi-Hsuan Yang, and Juhan Nam
  Proceedings of the New Interfaces for Musical Expression (NIME), 2021 [paper] [code] [demo] [video]

2020

Journals

• Semantic Tagging of Singing Voices in Popular Music Recordings
  Keunhyoung Luke Kim, Jongpil Lee, Sangeun Kum, Chae Lin Park, and Juhan Nam
  IEEE/ACM Transactions on Audio, Speech and Language Processing, 2020 [paper] [website/dataset]
• Note Intensity Estimation of Piano Recordings Using Coarsely-aligned MIDI Score
  Dasaem Jeong, Taegyun Kwon, and Juhan Nam
  Journal of the Audio Engineering Society, 2020 [paper]
• Novelty and Influence of Creative Works, and Quantifying Patterns of Advances Based On Probabilistic References Networks
  Doheum Park, Juhan Nam, and Juyong Park
  EPJ Data Science, 2020 [paper]

Conferences and Workshops

• TräumerAI: Dreaming Music with StyleGAN
  Dasaem Jeong, Seungheon Doh, and Taegyun Kwon
  Workshop on Machine Learning for Creativity and Design, Neural Information Processing Systems (NeurIPS), 2020 [paper]
• Drum Sample Retrieval from Mixed Audio via a Joint Embedding Space of Mixed and Single Audio Samples
  Wonil Kim and Juhan Nam
  Proceedings of the 149th Audio Engineering Society Convention (AES), 2020 [paper]
• Children's Song Dataset for Singing Voice Research
  Soonbeom Choi, Wonil Kim, Saebyul Park, Sangeon Yong, and Juhan Nam
  Late Breaking Demo in the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 [html] [dataset]
• PyTSMod: A Python Implementation of Time-Scale Modification Algorithms
  Sangeon Yong, Soonbeom Choi, and Juhan Nam
  Late Breaking Demo in the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 [html] [code]
• A Computational Analysis of Real-World DJ Mixes using Mix-To-Track Subsequence Alignment
  Taejun Kim, Minsuk Choi, Evan Sacks, Yi-Hsuan Yang, and Juhan Nam
  Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 [paper] [code] [poster] [video]
• Polyphonic Piano Transcription Using Autoregressive Multi-State Note Model
  Taegyun Kwon, Dasaem Jeong, and Juhan Nam
  Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 [paper]
• Metric Learning VS Classification for Disentangled Music Representation Learning
  Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan Nam
  Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 [paper]
• Semi-Supervised Learning Using Teacher-Student Models for Vocal Melody Extraction
  Sangeun Kum, Jing-Hua Lin, Li Su, and Juhan Nam
  Proceedings of the 21st International Society for Music Information Retrieval Conference (ISMIR), 2020 [paper]
• Musical Word Embedding: Bridging the Gap between Listening Contexts and Music
  Seungheon Doh, Jongpil Lee, Tae Hong Park, and Juhan Nam
  Machine Learning for Media Discovery Workshop, International Conference on Machine Learning (ICML), 2020 [paper] [website]
• Disentangled Multidimensional Metric Learning for Music Similarity
  Jongpil Lee, Nicholas J. Bryan, Justin Salamon, Zeyu Jin, and Juhan Nam
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 [paper] [dataset]
  *** IEEE SPS Student Travel Grant ***
• Korean Singing Voice Synthesis Based on Auto-Regressive Boundary Equilibrium GAN
  Soonbeom Choi, Wonil Kim, Saebyul Park, Sangeon Yong, and Juhan Nam
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2020 [paper] [website] [code]

2019

Journals

• Comparison and Analysis of SampleCNN Architectures for Audio Classification
  Taejun Kim, Jongpil Lee, and Juhan Nam
  IEEE Journal of Selected Topics in Signal Processing, 2019 [paper] [code]
• Introduction to the Issue on Data Science: Machine Learning for Audio Signal Processing (Editorial)
  Hendrik Purwins, Bob Sturm, Bo Li, Juhan Nam, and Abeer Alwan
  IEEE Journal of Selected Topics in Signal Processing, 2019 [paper]
• Joint Detection and Classification of Singing Voice Melody Using Convolutional Recurrent Neural Networks
  Sangeun Kum and Juhan Nam
  Applied Sciences, 2019 [paper] [code]

Conferences and Workshops

• A Cross-Scape Plot Representation for Visualizing Symbolic Melodic Similarity
  Saebyul Park, Taegyun Kwon, Jongpil Lee, Jeounghoon Kim, and Juhan Nam
  Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019 [paper] [code]
• VirtuosoNet: A Hierarchical RNN-based System for Modeling Expressive Piano Performance
  Dasaem Jeong, Taegyun Kwon, Yoojin Kim, Kyogu Lee and Juhan Nam
  Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019 [paper] [code]
• Zero-shot Learning for Audio-based Music Classification and Tagging
  Jeong Choi, Jongpil Lee, Jiyoung Park, and Juhan Nam
  Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019 [paper] [code]
• Learning a Joint Embedding Space of Monophonic and Mixed Music Signals for Singing Voice
  Kyungyun Lee and Juhan Nam
  Proceedings of the 20th International Society for Music Information Retrieval Conference (ISMIR), 2019 [paper] [website] [code]
• SMPD: Symbolic Music Plagiarism Dataset
  Saebyul Park, Halla Kim, Juyong Park, Jeounghoon Kim, and Juhan Nam
  The Seventh Seminar on Cognitively Based Music Informatics Research (CogMIR), 2019
• Zero-shot Learning and Knowledge Transfer in Music Classification and Tagging
  Jeong Choi, Jongpil Lee, Jiyoung Park, and Juhan Nam
  Machine Learning for Music Discovery Workshop, the 36th International Conference on Machine Learning (ICML), 2019 [paper]
• Representation Learning of Music Using Artist, Album, and Track information
  Jongpil Lee, Jiyoung Park, and Juhan Nam
  Machine Learning for Music Discovery Workshop, the 36th International Conference on Machine Learning (ICML), 2019 [paper]
• Graph Neural Network for Music Score Data and Modeling Expressive Piano Performance
  Dasaem Jeong, Taegyun Kwon, Yoojin Kim, and Juhan Nam
  Proceedings of the 36th International Conference on Machine Learning (ICML), 2019 [paper]
• Sonicanvas : An Audio Reactive Graphics Created Along Frequency Band
  Taewan Kim and Juhan Nam
  Proceedings of the 25th International symposium on electronic art (ISEA), 2019 (poster) [video]
• Easy Jazz: Web-based Jazz Improvisation System
  Wonil Kim and Juhan Nam
  Proceedings of the 25th International symposium on electronic art (ISEA), 2019 (poster) [website]
• MeloDraw: A System for Melodic Contour Search from Embedded Space Using Line Drawings
  Jeong Choi, Chaelin Park, Halla Kim, Wonil Kim, and Juhan Nam
  Proceedings of the 25th International symposium on electronic art (ISEA), 2019 (poster) [website]
• Score and Performance Features for Rendering Expressive Music Performances
  Dasaem Jeong, Taegyun Kwon, Yoojin Kim, and Juhan Nam
  Proceedings of the Music Encoding Conference, 2019 [paper]

Domestic

• 가창 음원의 음악적 표현 이식 시스템
  용상언, 남주한
  한국 음성 학회, 2019
• Conditional GAN 기반 가창 합성 시스템
  최순범, 남주한
  한국 음성 학회, 2019

2018

Journals

• Deep Learning for Audio-based Music Classification and Tagging
  Juhan Nam, Keunwoo Choi, Jongpil Lee, Szu-Yu Chou, and Yi-Hsuan Yang
  IEEE Signal Processing Magazine, 2018 [paper]
• SampleCNN: End-to-End Deep Convolutional Neural Networks Using Very Small Filters for Music Classification
  Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan Nam
  Applied Sciences, 2018 [paper]

Conferences and Workshops

• VirtuosoNet: A Hierarchical Attention RNN for Generating Expressive Piano Performance from Music Score
  Dasaem Jeong, Taegyun Kwon, and Juhan Nam
  Workshop on Machine Learning for Creativity and Design, Neural Information Processing Systems (NeurIPS), 2018 [paper]
• Use the Force: Incorporating Touch Force Sensors into Mobile Music Interaction
  Edward Jangwon Lee, Sangeon Yong, Soonbeom Choi, Liwei Chan, Roshan Peiris, and Juhan Nam
  Lecture Notes in Computer Science (revised selected papers of CMMR 2017), Vol. 11265, 2018 [paper]
• Representation Learning of Music Using Artist Labels
  Jiyoung Park, Jongpil Lee, Jangyeon Park, Jung-Woo Ha, and Juhan Nam
  Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018 [paper] [code]
• Revisiting Singing Voice Detection: a Quantitative Review and the Future Outlook
  Kyungyun Lee, Keunwoo Choi, and Juhan Nam
  Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018 [paper] [code]
• A Timbre-based Approach to Estimate Key Velocity from Polyphonic Piano Recordings
  Dasaem Jeong, Taegyun Kwon, and Juhan Nam
  Proceedings of the 19th International Society for Music Information Retrieval Conference (ISMIR), 2018 [paper]
• NEUROSCAPE: Artificial Soundscape Based on Multimodal Connections of Deep Neural Networks
  Seungsoon Park, Jongpil Lee, and Juhan Nam
  International Computer Music Conference (ICMC), 2018 (installation)
• A Hybrid of Deep Audio Feature and i-vector for Artist Recognition
  Jiyoung Park, Donghyun Kim, Jongpil Lee, Sangeun Kum, and Juhan Nam
  Joint Workshop on Machine Learning for Music, International Conference on Machine Learning (ICML), 2018 [paper]
• Singing Expression Transfer from One Voice to Another for a Given Song
  Sangeon Yong and Juhan Nam
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 [paper] [demo]
• Sample-level CNN Architectures for Music Auto-tagging Using Raw Waveforms
  Taejun Kim, Jongpil Lee, and Juhan Nam
  Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2018 [paper] [code]

Preprint

• Deep Content-User Embedding Model for Music Recommendation
  Jongpil Lee, Kyungyun Lee, Jiyoung Park, Jangyeon Park, and Juhan Nam
  arXiv preprint arXiv:1807.06786, 2018 [paper]

2017

Journals

• Multi-Level and Multi-Scale Feature Aggregation Using Pre-trained Convolutional Neural Networks for Music Auto-Tagging
  Jongpil Lee and Juhan Nam
  IEEE Signal Processing Letters, 2017 [paper]

Conferences and Workshops

• Raw Waveform-based Audio Classification Using Sample-level CNN Architectures
  Jongpil Lee, Taejun Kim, Jiyoung Park, and Juhan Nam
  Machine Learning for Audio Signal Processing Workshop, Neural Information Processing Systems (NIPS), 2017 [paper]
• Combining Multi-Scale Features Using Sample-level Deep Convolutional Neural Networks for Weakly Supervised Sound Event Detection
  Jongpil Lee, Jiyoung Park, Sangeun Kum, Youngho Jeong, and Juhan Nam
  Proceedings of the 2nd Workshop on Detection and Classification of Acoustic Scenes and Events (DCASE), 2017 [paper]
• Cross-cultural Transfer Learning Using Sample-level Deep Convolutional Neural Networks
  Jongpil Lee, Jiyoung Park, Chanju Kim, Adrian Kim, Jangyeon Park, Jung-Woo Ha, and Juhan Nam
  Music Information Retrieval Evaluation eXchange (MIREX) in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017 [paper]
  *** The 1st place in the four K-POP tasks across all algorithms submitted so far ***
• Representation Learning Using Artist labels for Audio Classification Tasks
  Jiyoung Park, Jongpil Lee, Jangyeon Park, Jung-Woo Ha, and Juhan Nam
  Music Information Retrieval Evaluation eXchange (MIREX) in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017 [paper]
  *** The 1st place in the Music Mood Classification task across all algorithms submitted so far ***
• PerformScore: Toward Performance Visualization With the Score on the Web Browser
  Dasaem Jeong, Taegyun Kwon, Chaelin Park, and Juhan Nam
  Late Breaking Demo in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017 [paper]
• Music Galaxy Hitchhiter: 3D Web Music Navigation Through Audio Space Trained with Tag and Artist Labels
  Dongwoo Suh, Kyungyun Lee, Jongpil Lee, Jiyoung Park, and Juhan Nam
  Late Breaking Demo in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017 [paper]
• Building K-POP Singing Voice Tag Dataset: A Progress Report
  KeunHyoung Luke Kim, Sangeun Kum, Chae Lin Park, Jongpil Lee, Jiyoung Park, and Juhan Nam
  Late Breaking Demo in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017 [paper]
• Automatic DJ Mix Generation Using Highlight Detection
  Adrian Kim, Soram Park, Jangyeon Park, Jung-Woo Ha, Taegyun Kwon, and Juhan Nam
  Late Breaking Demo in the 18th International Society for Musical Information Retrieval Conference (ISMIR), 2017 [paper]
• Use the Force: Incorporating Touch Force Sensors into Mobile Music Interaction
  Edward Jangwon Lee, Sangeon Yong, Soonbeom Choi, Liwei Chan, Roshan Peiris, and Juhan Nam
  Proceedings of the 13th International Symposium on Computer Music Multidisciplinary Research (CMMR), 2017 [paper] [demo]
• Multi-Level and Multi-Scale Feature Aggregation Using Sample-level Deep Convolutional Neural Networks for Music Classification
  Jongpil Lee and Juhan Nam
  Machine Learning for Music Discovery Workshop, the 34th International Conference on Machine Learning (ICML), 2017 [paper]
• How the Rhythm Is Actually Performed in the First Movement of the Beethoven’s Seventh Symphony
  Dasaem Jeong and Juhan Nam
  Proceedings of the 10th International Conference of Students of Systematic Musicology (SysMus), 2017 [paper]
• Sample-level Deep Convolutional Neural Networks for Music Auto-Tagging Using Raw Waveforms
  Jongpil Lee, Jiyoung Park, Keunhyoung Luke Kim, and Juhan Nam
  Proceedings of the 14th Sound and Music Computing Conference (SMC), 2017 [paper]
• Audio-to-Score Alignment Of Piano Music Using RNN-based Automatic Music Transcription
  Taegyun Kwon, Dasaem Jeong, and Juhan Nam
  Proceedings of the 14th Sound and Music Computing Conference (SMC), 2017 [paper] [demo]
• Note Intensity Estimation of Piano Recordings by Score-informed NMF
  Dasaem Jeong and Juhan Nam
  Proceedings of the Audio Engineering Society Conference on Semantic Audio (AES), 2017 [paper]
• ForceClicks: Enabling Efficient Button Interaction with Single Finger Touch
  Sangeon Yong, Edward Jangwon Lee, Roshan Peiris, Liwei Chan, and Juhan Nam
  Proceedings of the International Conference on Tangible, Embedded and Embodied Interactions (TEI), 2017 (work-in-progress) [paper] [demo]

Domestic

• 바이브레이션 리사주 도형을 이용한 노래 창법 시각화
  김태형, 남주한
  한국 HCI 학회, 2017

2016

Journals

• Augmenting Environmental Interaction in Audio Feedback Systems
  Seunghun Kim, Graham Wakefield, and Juhan Nam
  Applied Sciences, 2016 [paper]
• Sparse Feature Learning for Instrument Identification: Effects of Sampling and Pooling Methods
  Yoonchang Han, Subin Lee, Juhan Nam, and Kyogu Lee
  Journal of the Acoustical Society of America (JASA), 2016 [paper]

Conferences and Workshops

• Melody Extraction on Vocal Segments Using Multi-Column Deep Neural Networks
  Sangeun Kum, Changheun Oh, and Juhan Nam
  Proceedings of the 17th International Society for Music Information Retrieval Conference (ISMIR), 2016 [paper] [website]
• Comparison of Tonality Models in Measuring Chord Sequence Similarity
  Saebyul Park, Jeounghoon Kim, and Juhan Nam
  Proceedings of the 14th International Conference on Music Perception and Cognition (ICMPC), 2016 [paper]
• Characteristics of Non-linguistic Vocalizations as Auditory Emoticons
  Kyoungsoo Chun, Jinah Kwak, and Juhan Nam
  Proceedings of the 14th International Conference on Music Perception and Cognition (ICMPC), 2016 [paper]
• Sonic Participation in the Evolving Audio Feedback System
  Seunghun Kim, Changheun Oh, Graham Wakefield, and Juhan Nam
  Proceedings of The 22nd International Symposium on Electronic Art (ISEA), 2016 [paper] [demo]
• Visualizing Music in its Entirety using Acoustic Features: Music Flowgram
  Dasaem Jeong and Juhan Nam
  Proceedings of the 2nd International Conference on Technologies for Music Notation and Representation (TENOR), 2016 [paper]

Domestic

• 멜로디 추출 알고리즘으로 살펴보는 음악정보 검색
  금상은, 남주한
  대한전자공학회, 전자공학회지, 2016
• 한국가요 목소리 태그 검증과 가수 유사도 분석
  이종필, 김태형, 금상은, 김근형, 오창현, 남주한
  한국 음향 학회 춘계 학술 대회, 2016
• PSOLA 기법을 이용한 실시간 가창 음정 보정 시스템
  김태형, 남주한
  한국 음향 학회 춘계 학술 대회, 2016

2015

Conferences and Workshops

• Melodic and Harmonic Similarity for Music Plagiarism: Comparison between computational analysis and perceptual evaluation
  Saebyul Park, Seunghun Kim, Dasaem Jeong, Juhan Nam, and Jeounghoon Kim
  Proceedings of the Society for Music Perception and Cognition (SMPC), 2015
• Augmenting Room Acoustics and System Interaction for Intentional Control of Audio Feedback
  Seunghun Kim, Graham Wakefield, and Juhan Nam
  Proceedings of the 41st International Computer Music Conference (ICMC), 2015 [paper]
• SoniControl: Gesture Recognition System for Electric Guitar Using VLF Beacon Signals
  Sangwon Suh, Juhan Nam, and Sung-hee Lee
  Proceedings of the 15th International Conference on New Interfaces for Musical Expression (NIME), 2015 [paper]
• Toward Certain Sonic Properties of an Audio Feedback System by Evolutionary Control of Second-Order Structures
  Seunghun Kim, Juhan Nam, and Graham Wakefield
  Proceedings of the 4th International Conference (and 12th European event) on Evolutionary and Biologically Inspired Music, Sound, Art and Design (EvoMUSART), 2015 [paper] [demo]

Preprint

• A Deep Bag-of-Features Model for Music Auto-Tagging
  Juhan Nam, Jorge Herrera, and Kyogu Lee
  arXiv preprint arXiv:1508.04999, 2015 [paper]

Pre-MACLab

Journals

• Optimized Polynomial Spline Basis Function Design for Quasi-Bandlimited Classical Waveform Synthesis
  Jussi Pekonen, Juhan Nam, Vesa Välimäki, and Julius O. Smith
  IEEE Signal Processing Letters, 2012 [paper]
• Perceptually Informed Synthesis of Bandlimited Classical Waveforms Using Integrated Polynomial Interpolation
  Vesa Välimäki, Jussi Pekonen, and Juhan Nam
  Journal of the Acoustical Society of America (JASA), 2012 [paper]
• Efficient antialiasing oscillator algorithms using low-order fractional delay filters
  Juhan Nam, Vesa Välimäki, Jonathan S. Abel, and Julius O. Smith
  IEEE Transactions on Audio, Speech and Language Processing, 2010 [paper]
• Alias-suppressed oscillators based on differentiated polynomial waveforms
  Vesa Välimäki, Juhan Nam, Jonathan O. Smith, and Jonathan S. Abel
  IEEE Transactions on Audio, Speech and Language Processing, 2010 [paper]

Conferences and Workshops

• Acoustic Scene Classification Using Sparse Feature Learning and Event-based Pooling
  Kyogu Lee, Ziwon Hyung, and Juhan Nam
  Proceedings of the IEEE Workshop on Applications of Signal Processing to Audio and Acoustics (WASPAA), 2013 [paper]
• Learning Sparse Feature Representations for Music Annotation and Retrieval
  Juhan Nam, Jorge Herrera, Malcolm Slaney, and Julius O. Smith
  Proceedings of the 13th International Conference for Music Information Retrieval (ISMIR) Conference, 2012 [paper]
• Sound Recognition in Mixtures
  Juhan Nam, Gautham J. Mysore, and Paris Smaragdis
  Proceedings of the International Conference on Latent Variable Analysis and Signal Separation (LVA/ICA), 2012 [paper]
• A Classification-Based Polyphonic Piano Transcription Approach Using Learned Feature Representations
  Juhan Nam, Jiquan Ngiam, Honglak Lee, and Malcolm Slaney
  Proceedings of the 12th International Conference for Music Information Retrieval (ISMIR) Conference, 2011 [paper]
• Multimodal Deep Learning
  Jiquan Ngiam, Aditya Khosla, Mingyu Kim, Juhan Nam, Honglak Lee, and Andrew Y. Ng
  Proceedings of the 28th International Conference on Machine Learning (ICML), 2011 [paper]
• A super-resolution spectrogram using coupled PLCA
  Juhan Nam, Gautham Mysore, Joachim Ganseman, Kyogu Lee, and Jonathan S. Abel
  Proceedings of the 11th Conference of the International Speech Communication Association (InterSpeech), 2010 [paper]
• On Minimizing the Look-Up Table Size in Quasibandlimited Classical Waveform Oscillators
  Jussi Pekonen, Juhan Nam, Julius O. Smith, Jonathan S. Abel, and V. Välimäki
  Proceedings of the 13th Int. Conference on Digital Audio Effects (DAFx), 2010 [paper]
• Variable Fractional Delay Filters in Bandlimited Oscillator Algorithms for Music Synthesis
  Jussi Pekonen, Vesa Välimäki, Juhan Nam, Julius O. Smith, and Jonathan S. Abel
  Proceedings of Int. Conference on Green Circuits and Systems, 2010 (Invited paper) [paper]
• Alias-free virtual analog oscillators using a feedback delay loop
  Juhan Nam, Vesa Välimäki, Jonathan S. Abel, and Julius O. Smith
  Proceedings of the 12th Int. Conference on Digital Audio Effects (DAFx), 2009 [paper]
• A Method for Estimating Interaural Time Difference for Binaural Synthesis
  Juhan Nam, Jonathan S. Abel, and Julius O. Smith
  Proceedings of the 125th Audio Engineering Society Convention (AES), 2008 [paper]
• On the Minimum-phase Nature of Head-Related Transfer Functions
  Juhan Nam, Miriam A. Kolar, and Jonathan S. Abel
  Proceedings of the 125th Audio Engineering Society Convention (AES), 2008 [paper]

Domestic

• A Study of Sinusoid Generation Using Recursive Algorithms
  Juhan Nam
  Journal of Korea Electro-Acoustic Music Society (Emile), 2005

Patents

• Singing Expression Transplantation System
  Juhan Nam, Sangeon Yong
  US Patent, App. 16326649, 2019
• 주어진 악보에 대하여 다양한 스타일의 표현력 있는 피아노 연주를 생성하는 방법 및 장치
  남주한, 권태균, 정다샘, 김유진 출원 10-2020-0070101, 2020
• 파형 음원 신호를 분석하는 신경망 모델에 기반한 음원 분류 방법 및 분석 장치
  남주한, 이종필, 김태준 출원 10-2019-0130087, 2019
• 음원의 가수 목소리를 사용자의 음색으로 변환하는 시스템 및 방법
  남주한, 용상언, 출원 10-2018-0151531, 2018
• 심층 인공신경망 기반 자동 악보 채보를 이용한 연주 및 악보 정렬 방법 및 시스템
  남주한, 권태균, 정다샘 등록 10-1939001, 2019
• 가창 표현 이식 시스템
  남주한, 용상언, 등록 10-1966587, 2019
• 가창 표현 이식 시스템
  남주한, 용상언, 등록 10-1925217, 2018