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2020

[1]
R Agrawal and S Dixon. Learning frame similarity using siamese networks for audio-to-score alignment. Amsterdam, The Netherlands. [ bib ]
[2]
CS Armendariz, M Purver, S Pollak, N Ljubesic, M Ulcar, I Vulic, and MT Pilehvar. Semeval-2020 task 3: Graded word similarity in context. In A Herbelot, X Zhu, A Palmer, N Schneider, J May, and E Shutova, editors, SemEval@COLING, pages 36-49. International Committee for Computational Linguistics, 2020. [ bib | http ]
[3]
CS Armendariz, M Purver, M Ulčar, S Pollak, N Ljubešić, M Robnik-Šikonja, M Granroth-Wilding, and K Vaik. Cosimlex: A resource for evaluating graded word similarity in context. Marseille. [ bib | .pdf ]
[4]
M Bahameish and T Stockman. Fundamental considerations of hrv analysis in the development of real-time biofeedback systems. In Computing in Cardiology, volume 2020-September, Sep 2020. [ bib | DOI ]
[5]
N Banluesombatkul, P Ouppaphan, P Leelaarporn, P Lakhan, B Chaitusaney, N Jaimchariya, E Chuangsuwanich, W Chen, H Phan, N Dilokthanakul, and T Wilaiprasitporn. Metasleeplearner: A pilot study on fast adaptation of bio-signals-based sleep stage classifier to new individual subject using meta-learning. IEEE Journal of Biomedical and Health Informatics, PP, Nov 2020. [ bib | DOI | http ]
[6]
R Bianco, PMC Harrison, M Hu, C Bolger, S Picken, MT Pearce, and M Chait. Long-term implicit memory for sequential auditory patterns in humans. eLife, 9:1-6, May 2020. [ bib | DOI ]
[7]
L Bryce, M Sandler, S Serafin, and L Andersen. The sense of auditory presence in a choir for virtual reality. New York, Oct 2020. [ bib ]
[8]
O Chen, F Lipsmeier, H Phan, J Prince, K Taylor, C Gossens, M Lindemann, and M De Vos. Building a machine-learning framework to remotely assess parkinson's disease using smartphones. IEEE Transactions on Biomedical Engineering, pages 1-1, Apr 2020. [ bib | DOI ]
[9]
B Chettri, E Benetos, and BLT Sturm. Dataset artefacts in anti-spoofing systems: a case study on the asvspoof 2017 benchmark. IEEE/ACM Transactions on Audio, Speech and Language Processing, 28:3018-3028, Nov 2020. [ bib | DOI ]
[10]
B Chettri, T Kinnunen, and E Benetos. Deep generative variational autoencoding for replay spoof detection in automatic speaker verification. Computer Speech and Language, 63(101092), Sep 2020. [ bib | DOI ]
[11]
B Chettri, T Kinnunen, and E Benetos. Subband modeling for spoofing detection in automatic speaker verification. In http://www.odyssey2020.org/, pages 341-348. Tokyo, Japan, ISCA, Nov 2020. [ bib | DOI ]
[12]
A Clemente, M Vila-Vidal, MT Pearce, G Aguiló, G Corradi, and M Nadal. A set of 200 musical stimuli varying in balance, contour, symmetry, and complexity: Behavioral and computational assessments. Behavioral Research Methods, Feb 2020. [ bib | DOI | http ]
[13]
A Delgado Luezas, C Saitis, and M Sandler. Spectral and temporal timbral cues of vocal imitations of drum sounds. Sep 2020. [ bib ]
[14]
E Demirel, S Ahlback, and S DIxon. Automatic lyrics transcription using dilated convolutional neural networks with self-attention. In Proceedings of the International Joint Conference on Neural Networks, Jul 2020. [ bib | DOI ]
[15]
L Edlin, Y Liu, N Bryan-Kinns, and J Reiss. Exploring augmented reality as craft material. volume 12428 LNCS, pages 54-69. Jan 2020. [ bib | DOI ]
[16]
D Fano Yela, F Thalmann, V Nicosia, D Stowell, and M Sandler. Online visibility graphs: Encoding visibility in a binary search tree. Physical Review Research, 2(2), Apr 2020. [ bib | DOI ]
[17]
B Fields, T Stockman, LV Nickerson, and PGT Healey. Preface. In Proceedings of the 20th BCS HCI Group Conference: Engage, HCI 2006, page i, Jan 2020. [ bib ]
[18]
Y Gan, M Purver, and JR Woodward. A review of cross-domain text-to-sql models. In B Shmueli and YJ Huang, editors, AACL/IJCNLP (Student Research Workshop), pages 108-115. Association for Computational Linguistics, 2020. [ bib | http ]
[19]
E Gregoromichelaki, G Mills, C Howes, A Eshghi, S Chatzikyriakidis, M Purver, R Kempson, R Cann, and P Healey. Completability vs (in)completeness. Acta Linguistica Hafniensia, Oct 2020. [ bib | DOI | http ]
[20]
KO Hanlon and MB Sandler. The fifthnet chroma extractor. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, volume 2020-May, pages 3752-3756, May 2020. [ bib | DOI ]
[21]
PMC Harrison, R Bianco, M Chait, and MT Pearce. Ppm-decay: A computational model of auditory prediction with memory decay. PLoS Computational Biology, 16(11), Nov 2020. [ bib | DOI ]
[22]
PMC Harrison and MT Pearce. A computational cognitive model for the analysis and generation of voice leadings. Music Perception, 37(3):208-224, Feb 2020. [ bib | DOI ]
[23]
W Hu, T Ma, Y Wang, F Xu, and J Reiss. Tdcs: a new scheduling framework for real-time multimedia os. International Journal of Parallel, Emergent and Distributed Systems, 35(3):396-411, May 2020. [ bib | DOI ]
[24]
R Kim, S Thomas, RV Dierendonck, N Bryan-Kinns, and S Poslad. Working with nature's lag: Initial design lessons for slow biotic games. In GN Yannakakis, A Liapis, P Kyburz, V Volz, F Khosmood, and P Lopes, editors, FDG, pages 29:1-29:1. ACM, 2020. [ bib | http ]
[25]
P KUDUMAKIS, T WILMERING, M Sandler, V Rodríguez-Doncel, L Boch, and J Delgado. The challenge: From mpeg intellectual property rights ontologies to smart contracts and blockchains. IEEE: Signal Processing Magazine, 37(2):89-95, Feb 2020. [ bib | DOI ]
[26]
JH Lau, C Santos Armendariz, S Lappin, M Purver, and C Shu. How furiously can colourless green ideas sleep? sentence acceptability in context. Transactions of the Association for Computational Linguistics, 8:296-310, Jun 2020. [ bib | DOI | .pdf ]
[27]
J Lee and J Reiss. Real-time sound synthesis of audience applause. Journal of the Audio Engineering Society, 68(4):261-272, May 2020. [ bib | DOI ]
[28]
G Lepri, A Mcpherson, and J Bowers. Useless, not worthless: Absurd making as critical practice. In DIS 2020 - Proceedings of the 2020 ACM Designing Interactive Systems Conference, pages 1887-1899, Jul 2020. [ bib | DOI ]
[29]
G Lepri, A Mcpherson, A Nonnis, P Stapleton, K Andersen, T Mudd, J Bowers, P Bennett, and S Topley. Play make believe: Exploring design fiction and absurd making for critical nime. Jul 2020. [ bib | .pdf ]
[30]
A Light, PGT Healey, and G Simpson. Designing the not-quite-yet. In Proceedings of the 20th BCS HCI Group Conference: Engage, HCI 2006, pages 282-283, Jan 2020. [ bib ]
[31]
L Liu, A McLeod, S Sarkar, G Coleman, G Ruiz-Marcos, B Hayes, J Hentschel, D Shakespeare, I Harris, C Steinmetz, A Ragano, L Jovanovska, and X Li. Dmrn+15: Digital music research network workshop proceedings 2020. Online conference., Centre for Digital Music (C4DM), Dec 2020. [ bib | http ]
[32]
L Liu, G-V Morfi, and E Benetos. Joint piano-roll and score transcription for polyphonic piano music. London, UK, Dec 2020. [ bib | http ]
[33]
L Marinelli, A Lykartsis, S Weinzierl, and C Saitis. Musical dynamics classification with cnn and modulation spectra. Torino, Aug 2020. [ bib ]
[34]
A Martelloni, A Mcpherson, and M Barthet. Percussive fingerstyle guitar through the lens of nime: an interview study. Royal Birmingham Conservatoire. [ bib ]
[35]
M Martinez Ramirez, E Benetos, and J Reiss. Deep learning for black-box modeling of audio effects. Applied Sciences, 10(2), Jan 2020. [ bib | DOI | http ]
[36]
M Martinez Ramirez, E Benetos, and J Reiss. Modeling plate and spring reverberation using a dsp-informed deep neural network. pages 241-245. Barcelona, Spain, IEEE, May 2020. [ bib | DOI | http ]
[37]
S McGregor, M Purver, and G Wiggins. Metaphor generation through context sensitive distributional semantics. In Producing Figurative Expression, volume 10, pages 419-448. Nov 2020. [ bib | DOI ]
[38]
A Mcpherson and G Lepri. Beholden to our tools: Negotiating with technology while sketching digital instruments. Jun 2020. [ bib ]
[39]
A Mcpherson and K Tahiroglu. Idiomatic patterns and aesthetic influence in computer music languages. Organised Sound: an international journal of music and technology, 25(1). [ bib ]
[40]
C Metzig, M Gould, R Noronha, R Abbey, M Sandler, and C Colijn. Classification of origin with feature selection and network construction for folk tunes. Pattern Recognition Letters, 133:356-364, May 2020. [ bib | DOI ]
[41]
S MISHRA, E Benetos, B Sturm, and S Dixon. Reliable local explanations for machine listening. Glasgow, UK, IEEE, Jul 2020. [ bib | DOI | http ]
[42]
G Moro and A Mcpherson. A platform for low-latency continuous keyboard sensing and sound generation. In nime.org/archives. Royal Birmingham Conservatoire, Jul 2020. [ bib ]
[43]
A Mourgela, TR Agus, and JD Reiss. Investigation of a real-time hearing loss simulation for use in audio production. In 149th Audio Engineering Society Convention 2020, AES 2020, Jan 2020. [ bib ]
[44]
V-D Nguyen, H Phan, A Mansour, A Coatanhay, and T Marsault. On the proof of recursive vogler algorithm for multiple knife-edge diffraction. IEEE Transactions on Antennas and Propagation, pages 1-1, Nov 2020. [ bib | DOI ]
[45]
B O'Connor, S Dixon, and G Fazekas. An exploratory study on perceptual spaces of the singing voice. volume 1, Stockholm, Sweden, Oct 2020. Proceedings of the 2020 Joint Conference on AI Creativity. [ bib | http ]
[46]
A Pankajakshan, H Bear, V Subramanian, and E Benetos. Memory controlled sequential self attention for sound recognition. Shanghai, China, International Speech and Communication Association (ISCA), Oct 2020. [ bib | DOI ]
[47]
GG Peeters and JD Reiss. A deep learning approach to sound classification for film audio post-production. In 148th Audio Engineering Society International Convention, Jan 2020. [ bib ]
[48]
L Pham, H Phan, T Nguyen, R Palaniappan, A Mertins, and I McLoughlin. Robust acoustic scene classification using a multi-spectrogram encoder-decoder framework. Digital Signal Processing, pages 102943-102943, Dec 2020. [ bib | DOI ]
[49]
H Phan, OY Chen, P Koch, Z Lu, I McLoughlin, A Mertins, and M De Vos. Towards more accurate automatic sleep staging via deep transfer learning. IEEE Transactions on Biomedical Engineering, PP, Aug 2020. [ bib | DOI | http ]
[50]
H Phan, IV McLoughlin, L Pham, OY Chen, P Koch, M De Vos, and A Mertins. Improving gans for speech enhancement. IEEE Signal Processing Letters, 27:1700-1704, Sep 2020. [ bib | DOI ]
[51]
H Phan, K Mikkelsen, OY Chén, P Koch, A Mertins, P Kidmose, and M De Vos. Personalized automatic sleep staging with single-night data: a pilot study with kl-divergence regularization. Physiological Measurement, Jun 2020. [ bib | DOI ]
[52]
N Politimou, P Douglass-Kirk, M Pearce, L Stewart, and F Franco. Melodic expectations in 5- and 6-year-old children. Journal of Experimental Child Psychology, 203, Nov 2020. [ bib | DOI ]
[53]
P Proutskova, A Volk, P Heidarian, and G Fazekas. From music ontology towards ethno-music-ontology. In https://www.ismir2020.net/assets/img/proceedings/2020_ISMIR_Proceedings.pdf, pages 923-931. Montreal, Canada, Oct 2020. [ bib | http ]
[54]
DR Quiroga-Martinez, NC Hansen, A Højlund, M Pearce, E Brattico, and P Vuust. Decomposing neural responses to melodic surprise in musicians and non-musicians: Evidence for a hierarchy of predictions in the auditory system. NeuroImage, 215, Apr 2020. [ bib | DOI ]
[55]
DR Quiroga-Martinez, NC Hansen, A Højlund, M Pearce, E Brattico, and P Vuust. Musical prediction error responses similarly reduced by predictive uncertainty in musicians and non-musicians. European Journal of Neuroscience, Jan 2020. [ bib | DOI ]
[56]
A Ragano, E Benetos, and A Hines. Audio impairment recognition using a correlation-based feature representation. In http://qomex2020.ie/. Athlone, Ireland, IEEE, May 2020. [ bib | DOI ]
[57]
A Ragano, E Benetos, and A Hines. Development of a speech quality database under uncontrolled conditions. Shanghai, China, Oct 2020. [ bib | DOI ]
[58]
M Rohanian, J Hough, and M Purver. Multi-modal fusion with gating using audio, lexical and disfluency features for alzheimer's dementia recognition from spontaneous speech. In Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, volume 2020-October, pages 2187-2191, Oct 2020. [ bib | DOI ]
[59]
C Saitis and K Siedenburg. Brightness perception for musical instrument sounds: Relation to timbre dissimilarity and source-cause categories. The Journal of the Acoustical Society of America, 148(4):2256-2266, Oct 2020. [ bib | DOI ]
[60]
Pedro Sarmento, Ove Holmqvist, and Mathieu Barthet. Musical Smart City: Perspectives on Ubiquitous Sonification. In Proceedings of the 2020 Ubiquitous Music Workshop, 2020. [ bib ]
[61]
E Shatri and G Fazekas. Optical music recognition: State of the art and major challenges. Hamburg, May 2020. [ bib | http ]
[62]
R Shekhar, M Pranjić, S Pollak, A Pelicon, and M Purver. Automating news comment moderation with limited resources: Benchmarking in croatian and estonian. Journal of Language Technology and Computational Linguistics, 34(1):49-79, Sep 2020. [ bib | .pdf ]
[63]
F Soave, N Bryan-Kinns, and I Farkhatdinov. A preliminary study on full-body haptic stimulation on modulating self-motion perception in virtual reality. Aug 2020. [ bib ]
[64]
AM Solomes and D Stowell. Efficient bird sound detection on the bela embedded system. In ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings, volume 2020-May, pages 746-750, May 2020. [ bib | DOI ]
[65]
CJ Steinmetz and JD Reiss. Randomized overdrive neural networks. Dec 2020. [ bib ]
[66]
A Stockman and F Feng. Exploring crossmodal perceptual enhancement and integration in a sequence reproducing task with cognitive priming. Journal on Multimodal User Interfaces, Jul 2020. [ bib | DOI ]
[67]
A Stockman and S WILKIE. The effect of audio cues and sound source stimuli on the perception of approaching objects. Applied Acoustics, May 2020. [ bib | DOI ]
[68]
D Stoller, M Tian, S Ewert, and S Dixon. Seq-u-net: A one-dimensional causal u-net for efficient sequence modelling. In IJCAI International Joint Conference on Artificial Intelligence, volume 2021-January, pages 2893-2900, Jan 2020. [ bib ]
[69]
D Stowell, J Kelly, D Tanner, J Taylor, E Jones, J Geddes, and E Chalstrey. A harmonised, high-coverage, open dataset of solar photovoltaic installations in the uk. Scientific Data, 7(1), Dec 2020. [ bib | DOI ]
[70]
D Stowell and J Sueur. Ecoacoustics: acoustic sensing for biodiversity monitoring at scale. Remote Sensing in Ecology and Conservation, 6(3):217-219, Aug 2020. [ bib | DOI ]
[71]
V SUBRAMANIAN, A Pankajakshan, E Benetos, N Xu, S McDonald, and M Sandler. A study on the transferability of adversarial attacks in sound event classification. pages 301-305. Barcelona, Spain, IEEE, May 2020. [ bib | DOI | http ]
[72]
T Tabak and M Purver. Temporal mental health dynamics on social media. [ bib | http ]
[73]
T Tabak and M Purver. Temporal mental health dynamics on social media. In K Verspoor, KB Cohen, M Conway, BD Bruijn, M Dredze, R Mihalcea, and BC Wallace, editors, NLP4COVID@EMNLP. Association for Computational Linguistics, 2020. [ bib | DOI | http ]
[74]
A Thompson, G Fazekas, and G Wiggins. Poster: Programming practices among interactive audio software developers. In Proceedings of IEEE Symposium on Visual Languages and Human-Centric Computing, VL/HCC, volume 2020-August, Aug 2020. [ bib | DOI ]
[75]
L Turchet, F Antoniazzi, F Viola, F Giunchiglia, and G Fazekas. The internet of musical things ontology. Journal of Web Semantics, 60, Jan 2020. [ bib | DOI ]
[76]
L Turchet, G Fazekas, M Lagrange, HS Ghadikolaei, and C Fischione. The internet of audio things: State of the art, vision, and challenges. IEEE Internet of Things Journal, 7(10):10233-10249, May 2020. [ bib | DOI ]
[77]
L Turchet, J Pauwels, C Fischione, and G Fazekas. Cloud-smart musical instrument interactions. ACM Transactions on Internet of Things, 1(3):1-29, Jul 2020. [ bib | DOI ]
[78]
E Vidaña-Vila, J Navarro, C Borda-Fortuny, D Stowell, and RM Alsina-Pagès. Low-cost distributed acoustic sensor network for real-time urban sound monitoring. Electronics (Switzerland), 9(12):1-25, Dec 2020. [ bib | DOI ]
[79]
C Wang, V Lostanlen, E Benetos, and E Chew. Playing technique recognition by joint time–frequency scattering. pages 881-885. Barcelona, Spain, May 2020. [ bib | DOI ]
[80]
W Wang, N Bryan-Kinns, and JG Sheridan. On the role of in-situ making and evaluation in designing across cultures. CoDesign, 16(3):233-250, Jul 2020. [ bib | DOI ]
[81]
W Wei, H Zhu, E Benetos, and Y Wang. A-crnn: a domain adaptation model for sound event detection. pages 276-280. Barcelona, Spain, IEEE, May 2020. [ bib | DOI | http ]
[82]
D Williams, B Fazenda, V Williamson, and G Fazekas. On performance and perceived effort in trail runners using sensor control to generate biosynchronous music. Sensors (Basel, Switzerland), 20(16):1-14, Aug 2020. [ bib | DOI ]
[83]
T WILMERING, DJ MOFFAT, A Milo, and M Sandler. A history of audio effects. Applied Sciences, 10(3), Jan 2020. [ bib | DOI ]
[84]
G Wright and M Purver. Creative language generation in a society of engagement and reflection. Coimbra. [ bib ]
[85]
A Ycart and E Benetos. Learning and evaluation methodologies for polyphonic music sequence prediction with lstms. IEEE/ACM Transactions on Audio, Speech and Language Processing, 28(1):1328-1341, Dec 2020. [ bib | DOI ]
[86]
A Ycart, L Liu, E Benetos, and M Pearce. Investigating the perceptual validity of evaluation metrics for automatic piano music transcription. Transactions of the International Society for Music Information Retrieval, 3(1):68-81, Jun 2020. [ bib | DOI ]
[87]
A Ycart, L Liu, E Benetos, and MT Pearce. Musical features for automatic music transcription evaluation. Technical report, Apr 2020. Technical report. [ bib | http ]
[88]
A ZACHARAKIS, B Hayes, C Saitis, and K Pastiadis. Evidence for timbre space robustness to an uncontrolled online stimulus presentation. In Proceedings of the 2nd International Conference on Timbre, pages 129-132. Thessaloniki (Online), Sep 2020. [ bib ]
[89]
H Zhang, K Zhang, and N Bryan-Kinns. Exploiting the emotional preference of music for music recommendation in daily activities. In Proceedings - 2020 13th International Symposium on Computational Intelligence and Design, ISCID 2020, pages 350-353, Dec 2020. [ bib | DOI ]
[90]
Y Zhao, G Fazekas, and M Sandler. Identifying master violinists using note-level audio features. In Proceedings of the Sound and Music Computing Conferences, volume 2020-June, pages 185-192, Jan 2020. [ bib ]
[91]
I Zioga, PMC Harrison, MT Pearce, J Bhattacharya, and CDB Luft. Auditory but not audiovisual cues lead to higher neural sensitivity to the statistical regularities of an unfamiliar musical style. Journal of Cognitive Neuroscience, 32(12):2241-2259, Oct 2020. [ bib | DOI ]

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