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A fundamental characteristic of audio is its compositional nature.
Investigating bert’s knowledge of language: Five analysis methods with npis
Alex Warstadt, Yu Cao, Ioana Grosu, Wei Peng, Hagen Blix, Yining Nie, Anna Alsop, Shikha Bordia, Haokun Liu, Alicia Parrish, Sheng-Fu Wang, Jason Phang, Anhad Mohananey, Phu Mon Htut, Paloma Jeretic, and Samuel R. Bowman · 1909
Earlier work this paper cites.
Automatic musical genre classification of audio signals, 2001
George Tzanetakis, Georg Essl, and Perry Cook · 2001
Earlier work this paper cites.
The winograd schema challenge
Hector Levesque, Ernest Davis, and Leora Morgenstern · 2012
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A dataset and taxonomy for urban sound research
Justin Salamon, Christopher Jacoby, and Juan Pablo Bello · 2014
Earlier work this paper cites.
Assessing the ability of LSTMs to learn syntax-sensitive dependencies
Tal Linzen, Emmanuel Dupoux, and Yoav Goldberg · 2016
Earlier work this paper cites.
Audio set: An ontology and human-labeled dataset for audio events
Jort F Gemmeke, Daniel PW Ellis, Dylan Freedman, Aren Jansen, Wade Lawrence, R Channing Moore, Manoj Plakal, and Marvin Ritter · 2017
Earlier work this paper cites.
spaCy 2: Natural language understanding with Bloom embeddings, convolutional neural networks and incremental parsing
Matthew Honnibal and Ines Montani · 2017
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URL http://bbcsfx.acropolis.org.uk/
A dump of BBC’s sound effects library, 12 2018 · 2018
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Colorless green recurrent networks dream hierarchically
Kristina Gulordava, Piotr Bojanowski, Edouard Grave, Tal Linzen, and Marco Baroni · 2018
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Representation learning with contrastive predictive coding
Aaron van den Oord, Yazhe Li, and Oriol Vinyals · 2018
Earlier work this paper cites.
Gender bias in coreference resolution
Rachel Rudinger, Jason Naradowsky, Brian Leonard, and Benjamin Van Durme · 2018
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Learning from between-class examples for deep sound recognition
Yuji Tokozume, Yoshitaka Ushiku, and Tatsuya Harada · 2018
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Gender bias in coreference resolution: Evaluation and debiasing methods
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang · 2018
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Verb argument structure alternations in word and sentence embeddings
Katharina Kann, Alex Warstadt, Adina Williams, and Samuel R. Bowman · 2019
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Audiocaps: Generating captions for audios in the wild
Chris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, and Gunhee Kim · 2019
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Medley-solos-DB: a cross-collection dataset for musical instrument recognition, September 2019
Vincent Lostanlen, Carmine-Emanuele Cella, Rachel Bittner, and Slim Essid · 2019
Earlier work this paper cites.
Libritts: A corpus derived from librispeech for text-to-speech, 2019
Heiga Zen, Viet Dang, Rob Clark, Yu Zhang, Ron J. Weiss, Ye Jia, Zhifeng Chen, and Yonghui Wu · 2019
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Vggsound: A large-scale audio-visual dataset
Honglie Chen, Weidi Xie, Andrea Vedaldi, and Andrew Zisserman · 2020
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Clotho: An audio captioning dataset
Konstantinos Drossos, Samuel Lipping, and Tuomas Virtanen · 2020
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SyntaxGym: An online platform for targeted evaluation of language models
Jon Gauthier, Jennifer Hu, Ethan Wilcox, Peng Qian, and Roger Levy · 2020
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A systematic assessment of syntactic generalization in neural language models
Jennifer Hu, Jon Gauthier, Peng Qian, Ethan Wilcox, and Roger Levy · 2020
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Investigating novel verb learning in BERT: Selectional preference classes and alternation-based syntactic generalization
Tristan Thrush, Ethan Wilcox, and Roger Levy · 2020
Cited alongside, same era.
BLiMP: The benchmark of linguistic minimal pairs for English
Alex Warstadt, Alicia Parrish, Haokun Liu, Anhad Mohananey, Wei Peng, Sheng-Fu Wang, and Samuel R. Bowman · 2020
Cited alongside, same era.
Covr: A test-bed for visually grounded compositional generalization with real images
Ben Bogin, Shivanshu Gupta, Matt Gardner, and Jonathan Berant · 2021
Cited alongside, same era.
Back to square one: Artifact detection, training and commonsense disentanglement in the Winograd schema
Yanai Elazar, Hongming Zhang, Yoav Goldberg, and Dan Roth · 2021
Cited alongside, same era.
The benefit of temporally-strong labels in audio event classification
Shawn Hershey, Daniel PW Ellis, Eduardo Fonseca, Aren Jansen, Caroline Liu, R Channing Moore, and Manoj Plakal · 2021
Robust fine-tuning of zero-shot models
Mitchell Wortsman, Gabriel Ilharco, Jong Wook Kim, Mike Li, Simon Kornblith, Rebecca Roelofs, Raphael Gontijo Lopes, Hannaneh Hajishirzi, Ali Farhadi, Hongseok Namkoong, et al · 2022
Later among the works it cites.
Wav2clip: Learning robust audio representations from clip
Ho-Hsiang Wu, Prem Seetharaman, Kundan Kumar, and Juan Pablo Bello · 2022
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URL https://soundbible.com/
SoundBible - Free Sound Clips, Sound Bites, and Sound Effects, 2023 · 2023
Closest in time.
Musiclm: Generating music from text, 2023
Andrea Agostinelli, Timo I. Denk, Zalán Borsos, Jesse Engel, Mauro Verzetti, Antoine Caillon, Qingqing Huang, Aren Jansen, Adam Roberts, Marco Tagliasacchi, Matt Sharifi, Neil Zeghidour, and Christian Frank · 2023
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Pengi: An audio language model for audio tasks, 2023
Soham Deshmukh, Benjamin Elizalde, Rita Singh, and Huaming Wang · 2023
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Clap learning audio concepts from natural language supervision
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Cited alongside, same era.
Clipcap: Clip prefix for image captioning
Ron Mokady, Amir Hertz, and Amit H Bermano · 2021
Cited alongside, same era.
Macs - multi-annotator captioned soundscapes, July 2021
Irene Martin Morato and Annamaria Mesaros · 2021
Cited alongside, same era.
Audio retrieval with natural language queries
Andreea-Maria Oncescu, A Koepke, Joao F Henriques, Zeynep Akata, and Samuel Albanie · 2021
Cited alongside, same era.
Learning transferable visual models from natural language supervision
Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021
Cited alongside, same era.
Winogrande: An adversarial winograd schema challenge at scale
Keisuke Sakaguchi, Ronan Le Bras, Chandra Bhagavatula, and Yejin Choi · 2021
Cited alongside, same era.
Laion-400m: Open dataset of clip-filtered 400 million image-text pairs
Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021
Cited alongside, same era.
Masked language modeling and the distributional hypothesis: Order word matters pre-training for little
Koustuv Sinha, Robin Jia, Dieuwke Hupkes, Joelle Pineau, Adina Williams, and Douwe Kiela · 2021
Cited alongside, same era.
Benjamin Elizalde, Soham Deshmukh, Mahmoud Al Ismail, and Huaming Wang · 2023
Closest in time.
Text-to-audio generation using instruction tuned llm and latent diffusion model
Deepanway Ghosal, Navonil Majumder, Ambuj Mehrish, and Soujanya Poria · 2023
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Recap: Retrieval-augmented audio captioning, 2023
Sreyan Ghosh, Sonal Kumar, Chandra Kiran Reddy Evuru, Ramani Duraiswami, and Dinesh Manocha · 2023
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Finetune like you pretrain: Improved finetuning of zero-shot vision models
Sachin Goyal, Ananya Kumar, Sankalp Garg, Zico Kolter, and Aditi Raghunathan · 2023
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Make-an-audio: Text-to-audio generation with prompt-enhanced diffusion models
Rongjie Huang, Jiawei Huang, Dongchao Yang, Yi Ren, Luping Liu, Mingze Li, Zhenhui Ye, Jinglin Liu, Xiang Yin, and Zhou Zhao · 2023
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Crepe: Can vision-language foundation models reason compositionally?
Zixian Ma, Jerry Hong, Mustafa Omer Gul, Mona Gandhi, Irena Gao, and Ranjay Krishna · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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Guilherme Penedo, Quentin Malartic, Daniel Hesslow, Ruxandra Cojocaru, Alessandro Cappelli, Hamza Alobeidli, Baptiste Pannier, Ebtesam Almazrouei, and Julien Launay · 2023
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Sentence transformers
Nils Reimers · 2023
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Sonniss Game Audio, 2022
Sonniss Limited · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
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Audio-text models do not yet leverage natural language
Ho-Hsiang Wu, Oriol Nieto, Juan Pablo Bello, and Justin Salomon · 2023
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Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation
Yusong Wu*, Ke Chen*, Tianyu Zhang*, Yuchen Hui*, Taylor Berg-Kirkpatrick, and Shlomo Dubnov · 2023
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Large-scale contrastive language-audio pretraining with feature fusion and keyword-to-caption augmentation
Yusong Wu, Ke Chen, Tianyu Zhang, Yuchen Hui, Taylor Berg-Kirkpatrick, and Shlomo Dubnov · 2023
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When and why vision-language models behave like bags-of-words, and what to do about it?
Mert Yuksekgonul, Federico Bianchi, Pratyusha Kalluri, Dan Jurafsky, and James Zou · 2023
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