Publications

Highlights

(For a full list see below or go to HAL)

Eiffel Tower: A deep-sea underwater dataset for long-term visual localization

Images from four visits to the same hydrothermal vent edifice over the course of five years. Camera poses and a common geometry of the scene were estimated using navigation data and Structure-from-Motion. This serves as a reference when evaluating visual localization techniques. An analysis of the data provides insights about the major changes observed throughout the years.

Clémentin Boittiaux, Claire Dune, Maxime Ferrera, Aurélien Arnaubec, Ricard Marxer, Marjolaine Matabos, Loic Van Audenhaege, Vincent Hugel

The International Journal of Robotics Research

The data is made publicly available at seanoe.org/data/00810/92226/

Homography-Based Loss Function for Camera Pose Regression

A novel loss function which is based on a multiplane homography integration. This new function does not require prior initialization and only depends on physically interpretable hyperparameters. It minimizes best the mean square reprojection error during training when compared with existing loss functions.

Clémentin Boittiaux, Ricard Marxer, Claire Dune, Aurélien Arnaubec, Vincent Hugel

IEEE Robotics and Automation Letters

The code is made publicly available at https://github.com/clementinboittiaux/homography-loss-function

A corpus of audio-visual Lombard speech with frontal and profile views

A bi-view audiovisual Lombard speech corpus which can be used to support joint computational-behavioral studies in speech perception.

Najwa Alghamdi, Steve Maddock, Ricard Marxer, Jon Barker, Guy J. Brown

Journal of the Acoustical Society of America

Corpus available at The Audio-visual Lombard Grid Speech Corpus website

The impact of the Lombard effect on audio and visual speech recognition systems

Analysis of audio and visual Lombard speech using new 54 speaker database. New data on the inter-speaker variability of the Lombard effect. Measurement of the impact of Lombard mismatch in a noise robust speech recognition system. Detailed analysis of plain speech versus Lombard speech performance in well-adapted recognition system. Evidence that visual Lombard speech supports higher recognition performance than visual plain speech.

Ricard Marxer, Jon Barker, Najwa Alghamdi, Steve Maddock

Speech Communication

 

Full List

  1. Cuervo, S., & Marxer, R. (2023). On the Benefits of Self-supervised Learned Speech Representations for Predicting Human Phonetic Misperceptions. In INTERSPEECH 2023 (pp. 1788–1792). Dublin, Ireland: ISCA. https://doi.org/10.21437/Interspeech.2023-1476
  2. Moore, R. K., & Marxer, R. (2023). Progress and Prospects for Spoken Language Technology: Results from Five Sexennial Surveys. In INTERSPEECH 2023 (pp. 401–405). Dublin, Ireland: ISCA. https://doi.org/10.21437/Interspeech.2023-235
  3. Richards, F., Paiement, A., Xie, X., Sola, E., & Duc, P.-A. (2023). Panoptic Segmentation of Galactic Structures in LSB Images. In 18th International Conference on Machine Vision Applications. Hamamatsu, Shizuoka, Japan. Retrieved from https://hal.science/hal-04129549
  4. Best, P., Paris, S., Glotin, H., & Marxer, R. (2023). Deep audio embeddings for vocalisation clustering. PLoS ONE, 18(7), e0283396. https://doi.org/10.1371/journal.pone.0283396
  5. Sanz, P., Marín, R., López-Barajas, S., Solis, A., Marxer, R., & Hugel, V. (2023). 1st Year of running MIR at UJI. In OCEANS 2023 - Limerick (pp. 1–5). Limerick, Ireland: IEEE. https://doi.org/10.1109/OCEANSLimerick52467.2023.10244270
  6. Boittiaux, C., Dune, C., Arnaubec, A., Marxer, R., Ferrera, M., & Hugel, V. (2023). Long-term visual localization in deep-sea underwater environment. In ORASIS. Carqueiranne, France: Thanh Phuong Nguyen. Retrieved from https://hal.science/hal-04108737
  7. Gibbs, L., Bingham, R. J., & Paiement, A. (2023). A novel filtering method for geodetically-determined ocean surface currents using deep learning. Environmental Data Science. Retrieved from https://hal.science/hal-04285643
  8. Patris, J., Malige, F., Hamame, M., Glotin, H., Barchasz, V., Gies, V., … Buchan, S. (2023). Medium-term acoustic monitoring of small cetaceans in Patagonia, Chile. PeerJ, 11, e15292. https://doi.org/10.7717/peerj.15292
  9. Boittiaux, C., Dune, C., Ferrera, M., Arnaubec, A., Marxer, R., Matabos, M., … Hugel, V. (2023). Eiffel Tower: A Deep-Sea Underwater Dataset for Long-Term Visual Localization. The International Journal of Robotics Research. https://doi.org/10.1177/02783649231177322
  10. Sarano, F., Sarano, V., Tonietto, M.-L., Yernaux, A., Jung, J.-L., Arribart, M., … Adam, O. (2023). Nursing Behavior in Sperm Whales (Physeter macrocephalus). Animal Behavior and Cognition, 10(2), 105–131. https://doi.org/10.26451/abc.10.02.02.2023
  11. Cuervo, S., Łańcucki, A., Marxer, R., Rychlikowski, P., & Chorowski, J. (2022). Variable-rate hierarchical CPC leads to acoustic unit discovery in speech. In S. Koyejo, S. Mohamed, A. Agarwal, D. Belgrave, K. Cho, & A. Oh (Eds.), Advances in Neural Information Processing Systems 35 (NeurIPS 2022) (Vol. 35, pp. 34995–35006). New Orleans, United States: Curran Associates, Inc. Retrieved from https://hal.science/hal-04093636
  12. Dinar, F., Chayla, R., Paris, S., & Busvelle, E. (2022). A low-level set of stationary features dedicated to non-intrusive load monitoring. In International Conference on Systems and Control. Marseille, France. Retrieved from https://hal.science/hal-03855164
  13. Richards, F., Xie, X., Paiement, A., Sola, E., & Duc, P.-A. (2022). MULTI-SCALE GRIDDED GABOR ATTENTION FOR CIRRUS SEGMENTATION. In IEEE International Conference on Image Processing (ICIP). Bordeaux, France. https://doi.org/10.1109/ICIP46576.2022.9898045
  14. Lehnhoff, L., Glotin, H., Bernard, S., Dabin, W., Le Gall, Y., Menut, E., … Mérigot, B. (2022). Behavioural Responses of Common Dolphins Delphinus delphis to a Bio-Inspired Acoustic Device for Limiting Fishery By-Catch. Sustainability, 14(20), 13186. https://doi.org/10.3390/su142013186
  15. Hafsati, M., Bentounes, K., & Marxer, R. (2022). Blind Speech Separation Through Direction of Arrival Estimation Using Deep Neural Networks with a Flexibility on the Number of Speakers. In 2022 IEEE 24th International Workshop on Multimedia Signal Processing (MMSP) (pp. 1–5). Shanghai, China: IEEE. https://doi.org/10.1109/MMSP55362.2022.9949050
  16. Boittiaux, C., Marxer, R., Dune, C., Arnaubec, A., & Hugel, V. (2022). Homography-Based Loss Function for Camera Pose Regression. IEEE Robotics and Automation Letters, 7(3), 6242–6249. https://doi.org/10.1109/LRA.2022.3168329
  17. Rojas-cerda, C., Buchan, S. J., Branch, T. A., Malige, F., Patris, J., Hucke-gaete, R., & Staniland, I. (2022). Presence of Southeast Pacific blue whales ( Balaenoptera musculus ) off South Georgia in the South Atlantic Ocean. Marine Mammal Science, 38, 1425–1441. https://doi.org/10.1111/mms.12946
  18. Malige, F., Patris, J., Hauray, M., Giraudet, P., Glotin, H., & Noûs, C. (2022). Mathematical models of long term evolution of blue whale song types’ frequencies. Journal of Theoretical Biology, 548, 111184. https://doi.org/10.1016/j.jtbi.2022.111184
  19. Cuervo, S., Grabias, M., Chorowski, J., Ciesielski, G., Lancucki, A., Rychlikowski, P., & Marxer, R. (2022). Contrastive Prediction Strategies for Unsupervised Segmentation and Categorization of Phonemes and Words. In ICASSP 2022 - 2022 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 3189–3193). Singapore, France: IEEE. https://doi.org/10.1109/ICASSP43922.2022.9746102
  20. Poupard, M., Ferrari, M., Best, P., & Glotin, H. (2022). Passive acoustic monitoring of sperm whales and anthropogenic noise using stereophonic recordings in the Mediterranean Sea, North West Pelagos Sanctuary. Scientific Reports. Retrieved from https://hal.science/hal-03561786
  21. Almahasneh, M., Paiement, A., Xie, X., & Aboudarham, J. (2022). MSMT-CNN for solar active region detection with multi-spectral analysis. SN Computer Science. https://doi.org/10.1007/s42979-022-01088-y
  22. Sola, E., Duc, P.-A., Richards, F., Paiement, A., Urbano, M., Klehammer, J., … Mcconnachie, A. (2022). Characterization of low surface brightness structures in annotated deep images. Astronomy and Astrophysics - A&A, 662, A124. https://doi.org/10.1051/0004-6361/202142675
  23. Best, P., Marxer, R., Paris, S., & Glotin, H. (2022). Temporal evolution of the Mediterranean fin whale song. Scientific Reports, 12(1), 13565. https://doi.org/10.1038/s41598-022-15379-0
  24. Chetouani, M., Mandel-Briefer, E., Dassow, A., Marxer, R., Moore, R., Obin, N., & Stowell, D. (2021). Proceedings of the 3rd International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots (VIHAR 2021). Retrieved from https://hal.science/hal-03429487
  25. Poupard, M., Symonds, H., Spong, P., & Glotin, H. (2021). Intra-Group Orca Call Rate Modulation Estimation Using Compact Four Hydrophones Array. Frontiers in Marine Science. Retrieved from https://hal.science/hal-03555012
  26. Joly, A., Goëau, H., Kahl, S., Picek, L., Lorieul, T., Cole, E., … Müller, H. (2021). Overview of LifeCLEF 2021: an evaluation of Machine-Learning based Species Identification and Species Distribution Prediction. In K. S. Candan, B. Ionescu, L. Goeuriot, B. Larsen, H. Müller, A. Joly, … N. Ferro (Eds.), CLEF 2021 - 12th International Conference of the CLEF Association (Vol. LNCS. LNISA - 12880, pp. 371–393). Virtual Event, France: Springer International Publishing. https://doi.org/10.1007/978-3-030-85251-1_24
  27. Marxer, R., Hugel, V., Prud’Homme, K. P., Batista, P., Aviles, J. V. M., Pascoal, A., … Schjolberg, I. (2021). Marine and Maritime Intelligent Robotics (MIR). In OCEANS 2021: San Diego – Porto. San Diego, France: IEEE. https://doi.org/10.23919/OCEANS44145.2021.9706122
  28. Chorowski, J., Ciesielski, G., Dzikowski, J., Łańcucki, A., Marxer, R., Opala, M., … Stypulkowski, M. (2021). Information Retrieval for ZeroSpeech 2021: The Submission by University of Wroclaw. In Interspeech 2021 (pp. 971–975). Brno, Czech Republic: ISCA. https://doi.org/10.21437/Interspeech.2021-1465
  29. Chorowski, J., Ciesielski, G., Dzikowski, J., Łańcucki, A., Marxer, R., Opala, M., … Stypulkowski, M. (2021). Aligned Contrastive Predictive Coding. In Interspeech 2021 (pp. 976–980). Brno, Czech Republic: ISCA. https://doi.org/10.21437/interspeech.2021-1544
  30. Hernaez, I., González-López, J. A., Navas, E., Pérez Córdoba, J. L., Saratxaga, I., Olivares, G., … Diener, L. (2021). Voice Restoration with Silent Speech Interfaces (ReSSInt). In IberSPEECH 2021 (pp. 130–134). Valladolid, Spain: ISCA. https://doi.org/10.21437/IberSPEECH.2021-28
  31. Almahasneh, M., Paiement, A., Xie, X., & Aboudarham, J. (2021). Active region detection in multi-spectral solar images. In International Conference on Pattern Recognition Applications and Methods (ICPRAM). online, Austria. Retrieved from https://hal.science/hal-03040990
  32. Almahasneh, M., Paiement, A., Xie, X., & Aboudarham, J. (2021). MLMT-CNN for Object Detection and Segmentation in Multi-layer and Multi-spectral Images. Machine Vision and Applications, 33, 9. https://doi.org/10.1007/s00138-021-01261-y
  33. Ferrari, M., Glotin, H., Oger, M., Marxer, R., Asch, M., Gies, V., & Sarano, F. (2020). 3D diarization of a sperm whale click cocktail party by an ultra high sampling rate portable hydrophone array for assessing individual cetacean growth curves. In Forum Acusticum (pp. 3239–3243). Lyon, France. https://doi.org/10.48465/fa.2020.1097
  34. Ferrari, M., Glotin, H., & Marxer, R. (2020). End to end raw audio deep learning of transients, application to bioacoustics. In e-Forum Acusticum 2020 (pp. 3245–3247). Lyon, France. https://doi.org/10.48465/fa.2020.1096
  35. Ferrari, M., Glotin, H., Oger, M., Marxer, R., Asch, M., Gies, V., & Sarano, F. (2020). 3D diarization of a sperm whale click cocktail party by an ultra high sampling rate portable hydrophone array for assessing individual cetacean growth curves. In FA2020. Lyon, France. Retrieved from https://hal.science/hal-03078655
  36. Ferrari, M., Glotin, H., & Marxer, R. (2020). END TO END RAW AUDIO DEEP LEARNING OF TRANSIENTS, APPLICATION TO BIOACOUSTICS. In FA2020 (Congrès Français d’Acoustique ). Lyon, France. Retrieved from https://hal.science/hal-03078665
  37. Best, P., Marzetti, S., Poupard, M., Ferrari, M., Paris, S., Marxer, R., … Glotin, H. (2020). Stereo to five-channels bombyx sonobuoys: from four years cetacean monitoring to real-time whale-ship anti-collision system. In e-Forum Acusticum 2020 (pp. 3229–3231). Lyon, France. https://doi.org/10.48465/fa.2020.1089
  38. Malige, F., Djokic, D., Patris, J., Sousa-Lima, R., & Glotin, H. (2020). Use of recurrence plots for identification and extraction of patterns in humpback whale song recordings. Bioacoustics, 1–16. https://doi.org/10.1080/09524622.2020.1845240
  39. Khurana, S., Laurent, A., Hsu, W.-N., Chorowski, J., Łańcucki, A., Marxer, R., & Glass, J. (2020). A Convolutional Deep Markov Model for Unsupervised Speech Representation Learning. In Interspeech 2020. Shanghai, China. Retrieved from https://hal.science/hal-02912029
  40. Dolfing, H. J. G. A., Jérome, B., Chorowski, J., Marxer, R., & Laurent, A. (2020). The ”ScribbleLens” Dutch historical handwriting corpus. In International Conference on Frontiers of Handwriting Recognition (ICFHR). Dortmund, Germany. Retrieved from https://hal.science/hal-02877520
  41. Jenkins, J., Paiement, A., Aboudarham, J., & Bonnin, X. (2020). Physics-informed detection and segmentation of type II solar radio bursts. In British Machine Vision Virtual Conference. Virtual, United Kingdom. Retrieved from https://inria.hal.science/hal-02923001
  42. Ferrari, M., Glotin, H., Marxer, R., & Asch, M. (2020). DOCC10: Open access dataset of marine mammal transient studies and end-to-end CNN classification. In IJCNN. Glasgow, United Kingdom. Retrieved from https://hal.science/hal-02866091
  43. Łańcucki, A., Chorowski, J., Sanchez, G., Marxer, R., Chen, N., Dolfing, H. J. G. A., … Laurent, A. (2020). Robust Training of Vector Quantized Bottleneck Models. In IJCNN 2020. Glasgow, United Kingdom. Retrieved from https://hal.science/hal-02912027
  44. Best, P., Ferrari, M., Poupard, M., Paris, S., Marxer, R., Symonds, H., … Glotin, H. (2020). Deep Learning and Domain Transfer for Orca Vocalization Detection. In International joint conference on neural networks. glasgow, United Kingdom. Retrieved from https://hal.science/hal-02865300
  45. Sanchez, G., Guis, V., Marxer, R., & Bouchara, F. (2020). Deep learning classification with noisy labels. In ICME Workshop. Londres, United Kingdom. Retrieved from https://hal.science/hal-02552375
  46. Poupard, M., de Montgolfier, B., & Glotin, H. (2020). Ethoacoustic by bayesian non parametric and stochastic neighbor embedding to forecast anthropic pressure on dolphins. In OCEANS. Marseille, France. Retrieved from https://hal.science/hal-02445440
  47. Patris, J., Buchan, S. J., Stafford, K. M., Findlay, K., Hucke-Gaete, R., Neira, S., … Malige, F. (2020). Inter-annual decrease in pulse rate and peak frequency of Southeast Pacific blue whale song types. Scientific Reports. https://doi.org/10.1038/s41598-020-64613-0
  48. Joly, A., Goëau, H., Botella, C., Ruiz de Castaneda, R., Glotin, H., Cole, E., … Müller, H. (2020). LifeCLEF 2020 Teaser: Biodiversity Identification and Prediction Challenges. In ECIR 2020 - 42nd European Conference on IR Research on Advances in Information Retrieval (Vol. Lecture Notes in Computer Science, pp. 542–549). Lisbon, Portugal. https://doi.org/10.1007/978-3-030-45442-5_70
  49. Sardari, F., Paiement, A., Hannuna, S., & Mirmehdi, M. (2020). VI-Net: View-Invariant Quality of Human Movement Assessment. Sensors. Retrieved from https://hal.science/hal-02934456
  50. Chorowski, J., Chen, N., Marxer, R., Dolfing, H. J. G. A., Łańcucki, A., Sanchez, G., … Laurent, A. (2019). Unsupervised Neural Segmentation and Clustering for Unit Discovery in Sequential Data. In NeurIPS 2019 workshop - Perception as generative reasoning - Structure, Causality, Probability. Vancouver, Canada. Retrieved from https://hal.science/hal-02399138
  51. Djokic, D., Oña, J., Buchan, S., Širović, A., Duque Mesa, E., May-Collado, L., … Sousa-Lima, R. (2019). Building A Dictionary Of Humpback Whale Song Units As A Tool For Assessing Stock Interactions Summary. World marine mammal conference 2019. Retrieved from https://hal.science/hal-02547084
  52. Morfi, V., Bas, Y., Pamula, H., Glotin, H., & Stowell, D. (2019). NIPS4Bplus: a richly annotated birdsong audio dataset. PeerJ Computer Science, 5, e223. https://doi.org/10.7717/peerj-cs.223
  53. Patris, J., Malige, F., Glotin, H., Asch, M., & Buchan, S. (2019). A standardized method of classifying pulsed sounds and its application to pulse rate measurement of blue whale southeast Pacific song units. Journal of the Acoustical Society of America, 146(4), 2145–2154. https://doi.org/10.1121/1.5126710
  54. Dassow, A., Marxer, R., Moore, R., & Stowell, D. (2019). Proceedings of the 2nd International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots (VIHAR 2019). Retrieved from https://hal.science/hal-03609831
  55. Sardari, F., Paiement, A., & Mirmehdi, M. (2019). View-invariant Pose Analysis for Human Movement Assessment from RGB Data. In 20th International Conference on Image Analysis and Processing (ICIAP). Trento, Italy. https://doi.org/10.1007/978-3-030-30645-8_22
  56. Ferrari, M., Marxer, R., Asch, M., & Glotin, H. (2019). Wave Propagation in the Biosonar Organ of sperm whales using a Finite Difference Time Domain method. In VIHAR. Lodon, United Kingdom. Retrieved from https://hal.science/hal-02445408
  57. Poupard, M., Best, P., Schlüter, J., Symonds, H., Spong, P., Lengagne, T., … Glotin, H. (2019). Large-scale unsupervised clustering of Orca vocalizations: a model for describing Orca communication systems. In 2nd International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots. Londres, United Kingdom. https://doi.org/10.7287/peerj.preprints.27979v1
  58. Ferrari, M., Glotin, H., Marxer, R., Barchasz, V., Sarano, V., Gies, V., … Sarano, F. (2019). High-frequency Near-field Physeter macrocephalus Monitoring by Stereo-Autoencoder and 3D Model of Sonar Organ. In OCEANS 2019. Marseille, France. Retrieved from https://hal.science/hal-02313898
  59. Ferrari, M., Poupard, M., Giraudet, P., Marxer, R., Prévot, J.-M., Soriano, T., & Glotin, H. (2019). Efficient artifacts filter by density-based clustering in long term 3D whale passive acoustic monitoring with five hydrophones fixed under an Autonomous Surface Vehicle. In OCEANS 2019 (p. 39). Marseille, France. https://doi.org/10.1109/OCEANSE.2019.8867416
  60. Patris, J., Komatitsch, D., Sepúlveda, M., Santos, M., Glotin, H., Malige, F., … Asch, M. (2019). Mono-hydrophone localization of baleen whales: a study of propagation using a spectral element method applied in Northern Chile. In Oceans 2019. Marseille, France. https://doi.org/10.1109/OCEANSE.2019.8867333
  61. Poupard, M., Best, P., Schlüter, J., Prévot, J.-M., Symonds, H., Spong, P., & Glotin, H. (2019). Deep Learning for Ethoacoustics of Orcas on three years pentaphonic continuous recording at Orcalab revealing tide, moon and diel effects. In OCEANS. Marseille, France. Retrieved from https://hal.science/hal-02445426
  62. Roger, V. (2019). Comment adapter les systèmes d’apprentissages modernes pour les données et problèmes en oncologie? In 1st workshop eSanté : Données, Big Data & IA en Oncologie. Toulouse, France. Retrieved from https://hal.science/hal-03003825
  63. Poupard, M., Ferrari, M., Schlüter, J., Marxer, R., Giraudet, P., Barchasz, V., … Glotin, H. (2019). REAL-TIME PASSIVE ACOUSTIC 3D TRACKING OF DEEP DIVING CETACEAN BY SMALL NON-UNIFORM MOBILE SURFACE ANTENNA. In 2019 IEEE International Conference on Acoustics, Speech and Signal Processing. Brighton, United Kingdom. Retrieved from https://hal.science/hal-02445414
  64. Bouchard, B., Barnagaud, J.-Y., Poupard, M., Glotin, H., Gauffier, P., Torres Ortiz, S., … Aurélie, C. (2019). Behavioural responses of humpback whales to food-related chemical stimuli. PLoS ONE, 14(2), e0212515. https://doi.org/10.1371/journal.pone.0212515
  65. Cooke, M., García Lecumberri, M. L., Barker, J., & Marxer, R. (2019). Lexical frequency effects in English and Spanish word misperceptions. Journal of the Acoustical Society of America, 145(2), EL136–EL141. https://doi.org/10.1121/1.5090196
  66. Joly, A., Goëau, H., Glotin, H., Spampinato, C., Bonnet, P., Vellinga, W.-P., … Müller, H. (2019). Biodiversity Information Retrieval Through Large Scale Content-Based Identification: A Long-Term Evaluation. In N. Ferro & C. Peters (Eds.), Information Retrieval Evaluation in a Changing World: Lessons Learned from 20 Years of CLEF (Vol. 41, pp. 389–413). Springer. https://doi.org/10.1007/978-3-030-22948-1_16
  67. Yordanova, K., Lüdtke, S., Whitehouse, S., Krüger, F., Paiement, A., Mirmehdi, M., … Kirste, T. (2019). Analysing Cooking Behaviour in Home Settings: Towards Health Monitoring. Sensors. Retrieved from https://hal.science/hal-02003387
  68. Morgan, J., Paiement, A., Seisenberger, M., Williams, J., & Wyner, A. (2018). A Chatbot Framework for the Children’s Legal Centre. In The 31st international conference on Legal Knowledge and Information Systems (JURIX). Groningen, Netherlands. Retrieved from https://hal.science/hal-01878545
  69. Gogate, M., Adeel, A., Marxer, R., Barker, J., & Hussain, A. (2018). DNN Driven Speaker Independent Audio-Visual Mask Estimation for Speech Separation. In Interspeech 2018 (pp. 2723–2727). Hybderabad, India: ISCA. https://doi.org/10.21437/Interspeech.2018-2516
  70. Balestriero, R., Cosentino, R., Glotin, H., & Baraniuk, R. (2018). Spline Filters For End-to-End Deep Learning. In 35th International Conference on Machine Learning. stockholm, Sweden. Retrieved from https://hal.science/hal-01879266
  71. Kobayashi, H. H., Kudo, H., Glotin, H., Roger, V., Poupard, M., Shimotoku, D., … Sezaki, K. (2018). A Real-Time Streaming and Detection System for Bio-acoustic Ecological Studies after the Fukushima Accident. In Multimedia Tools and Applications for Environmental & Biodiversity Informatics. Retrieved from https://hal.science/hal-01879592
  72. Patris, J., Malige, F., Djokic, D., Sousa-Lima, R., & Glotin, H. (2018). Humpback whale song theme recognition tool. DCLDE 2018. Retrieved from https://hal.science/hal-01868825
  73. Patris, J., Komatitsch, D., Asch, M., Buchan, S., Malige, F., & Glotin, H. (2018). Monohydrophone 3D localization of baleen whales. In DCLDE 2018. PARIS, France. Retrieved from https://hal.science/hal-01868824
  74. Ferrari, M., Marxer, R., Roger, V., Gies, V., Sarano, F., Asch, M., … Glotin, H. (2018). Sperm whales ultra high frequency near field multichannel analysis. The 8th International Workshop on Detection, Classification, Localization, and Density Estimation (DCLDE). Retrieved from https://hal.science/hal-01881615
  75. Malige, F., Patris, J., J., S., Stafford, K. M., Hucke-Gaete, R., Rendell, L., … Glotin, H. (2018). Joint analysis of pulsation and peak frequency : toward a new mathematical model for examining frequency decrease in pulsed blue whale song. In DCLDE 2018. PARIS, France. Retrieved from https://hal.science/hal-01868823
  76. Poupard, M., de Montgolfier, B., Roger, V., Lohani, D., & Glotin, H. (2018). EthoAcoustics : a model based on t-SNE & Clustering, ap-plied on Pantropical spotted dolphin during Whale Watching. 8th International DCLDE (Detection, Classification, Localization, and Density Estimation) Workshop. Retrieved from https://hal.science/hal-01873336
  77. Malige, F., Patris, J., Buchan, S. J., & Glotin, H. (2018). Acoustical analysis of submarine explosions in northern Chile on long terms continuous recordings. DCLDE 2018. Retrieved from https://hal.science/hal-01868827
  78. Alghamdi, N., Maddock, S., Marxer, R., Barker, J., & Brown, G. (2018). A corpus of audio-visual Lombard speech with frontal and profile views. Journal of the Acoustical Society of America, 143(6), EL523–EL529. https://doi.org/10.1121/1.5042758
  79. Marxer, R., Barker, J., Alghamdi, N., & Maddock, S. (2018). The impact of the Lombard effect on audio and visual speech recognition systems. Speech Communication, 100, 58–68. https://doi.org/10.1016/j.specom.2018.04.006
  80. Dassow, A., Marxer, R., & Moore, R. (2017). Proceedings of the 1st International Workshop on Vocal Interactivity in-and-between Humans, Animals and Robots (VIHAR 2017). Retrieved from https://hal.science/hal-03609819
  81. Martin, V., Bruno, E., & Murisasco, E. (2016). Predicting The French Stock Market Using Social Media Analysis. IJVCSN, International Journal of Virtual Communities and Social Networking, 8(15). Retrieved from https://amu.hal.science/hal-01479307
  82. Chollet, G., Amehraye, A., Razik, J., Zouari, L., Khemiri, H., & Mokbel, C. (2010). Spoken Dialogue in Virtual Worlds. In Development of Multimodal Interfaces: Active Listening and Synchrony. Springer. Retrieved from https://hal.science/hal-04094203
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