Built on

J. F. Gemmeke, D. P. Ellis, D. Freedman, A. Jansen, W. Lawrence, R. C. Moore, M. Plakal, and M. Ritter, “Audio set: An ontology and human-labeled dataset for audio events,” in
2017
Earlier work this paper cites.
C. D. Kim, B. Kim, H. Lee, and G. Kim, “Audiocaps: Generating captions for audios in the wild,” in
2019
Earlier work this paper cites.
K. Kilgour, M. Zuluaga, D. Roblek, and M. Sharifi, “Fréchet audio distance: A reference-free metric for evaluating music enhancement algorithms.” in
2019
Earlier work this paper cites.
Q. Kong, Y. Cao, T. Iqbal, Y. Wang, W. Wang, and M. D. Plumbley, “Panns: Large-scale pretrained audio neural networks for audio pattern recognition,”
2020
Earlier work this paper cites.
K. Choi, S. Oh, M. Kang, and B. McFee, “A proposal for foley sound synthesis challenge,”
Original
2022
Earlier work this paper cites.
K. Choi, J. Im, L. Heller, B. Mcfee, K. Imoto, Y. Okamoto, M. Lagrange, and S. Takamichi, “Foley sound synthesis at the dcase 2023 challenge,” in
2023
Earlier work this paper cites.
H. Liu, Z. Chen, Y. Yuan, X. Mei, X. Liu, D. Mandic, W. Wang, and M. D. Plumbley, “AudioLDM: Text-to-audio generation with latent diffusion models,”
Original
2023
Earlier work this paper cites.
M. Tailleur, J. Lee, M. Lagrange, K. Choi, L. M. Heller, K. Imoto, and Y. Okamoto, “Correlation of fréchet audio distance with human perception of environmental audio is embedding dependent,” in
2024
Earlier work this paper cites.
X. ZhiDong, L. XinYu, L. HaiCheng, Z. XiaoYan, and S. Yu, “Sound scene synthesis with audioldm and tango2 for dcase 2024 task7,” Samsung Research China-Nanjing, Nanjing, China, Tech. Rep., July 2024
2024
Earlier work this paper cites.
H. C. Chung and J. H. Jung, “Sound scene synthesis based on gan using contrastive learning and effective time-frequency swap cross attention mechanism,” KT Corporation, Seoul, Republic of Korea, Tech. Rep., July 2024
2024
Earlier work this paper cites.
Y. Yuan, H. Liu, X. Liu, M. D. Plumbley, and W. Wang, “Diffusion based sound scene synthesis for dcase challenge 2024 task 7,” University of Surrey, Guildford, United Kingdom, Tech. Rep., July 2024
2024
Earlier work this paper cites.
S. Ghosh, G. Verma, S. N. Shakya, S. Sharma, and S. Singh, “Sound scene synthesis based on fine-tuned latent diffusion model for dcase challenge 2024 task 7,” Indian Institute of Technology Mandi, Kamand, Mandi, India, Tech. Rep., July 2024
2024
Earlier work this paper cites.

Similar

J. Lee, M. Tailleur, L. M. Heller, K. Choi, M. Lagrange, B. McFee, K. Imoto, and Y. Okamoto, “Challenge on sound scene synthesis: Evaluating text-to-audio generation,” in
2024
Cited alongside, same era.
Y. Chung, J. Lee, and J. Nam, “T-foley: A controllable waveform-domain diffusion model for temporal-event-guided foley sound synthesis,” in
2024
Cited alongside, same era.
M. F. Colombo, F. Ronchini, L. Comanducci, and F. Antonacci, “Mambafoley: Foley sound generation using selective state-space models,”
Original
2024
Cited alongside, same era.
Z. Guo, J. Mao, R. Tao, L. Yan, K. Ouchi, H. Liu, and X. Wang, “Audio generation with multiple conditional diffusion model,” in
2024
Cited alongside, same era.
Z. Xie, X. Xu, Z. Wu, and M. Wu, “Picoaudio: Enabling precise timestamp and frequency controllability of audio events in text-to-audio generation,”

Then

Z. Xie, S. Yu, Q. He, and M. Li, “Sonicvisionlm: Playing sound with vision language models,” in
2024
Later among the works it cites.
J. Lee, J. Im, D. Kim, and J. Nam, “Video-foley: Two-stage video-to-sound generation via temporal event condition for foley sound,”
Original
2024
Later among the works it cites.
Y. Jeong, Y. Kim, S. Chun, and J. Lee, “Read, watch and scream! sound generation from text and video,”
Original
2024
Later among the works it cites.
A. Polyak, A. Zohar, A. Brown, A. Tjandra, A. Sinha, A. Lee, A. Vyas, B. Shi, C.-Y. Ma, C.-Y. Chuang,
Original
2024
Later among the works it cites.
Z. Chen, P. Seetharaman, B. Russell, O. Nieto, D. Bourgin, A. Owens, and J. Salamon, “Video-guided foley sound generation with multimodal controls,”
Original

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2025

Sound Scene Synthesis at the DCASE 2024 Challenge

Lagrange, Mathieu, Lee, Junwon, Tailleur, Modan et al.

Understand

This paper presents Task 7 at the DCASE 2024 Challenge: sound scene synthesis.

Recent advances in sound synthesis and generative models have enabled the creation of realistic and diverse audio content.
We introduce a standardized evaluation framework for comparing different sound scene synthesis systems, incorporating both objective and subjective metrics.
The challenge attracted four submissions, which are evaluated using the Fr\'echet Audio Distance (FAD) and human perceptual ratings.

Built on

J. F. Gemmeke, D. P. Ellis, D. Freedman, A. Jansen, W. Lawrence, R. C. Moore, M. Plakal, and M. Ritter, “Audio set: An ontology and human-labeled dataset for audio events,” in
2017
Earlier work this paper cites.
C. D. Kim, B. Kim, H. Lee, and G. Kim, “Audiocaps: Generating captions for audios in the wild,” in
2019
Earlier work this paper cites.
K. Kilgour, M. Zuluaga, D. Roblek, and M. Sharifi, “Fréchet audio distance: A reference-free metric for evaluating music enhancement algorithms.” in
2019
Earlier work this paper cites.
Q. Kong, Y. Cao, T. Iqbal, Y. Wang, W. Wang, and M. D. Plumbley, “Panns: Large-scale pretrained audio neural networks for audio pattern recognition,”
2020
Earlier work this paper cites.
K. Choi, S. Oh, M. Kang, and B. McFee, “A proposal for foley sound synthesis challenge,”
Original
2022
Earlier work this paper cites.
K. Choi, J. Im, L. Heller, B. Mcfee, K. Imoto, Y. Okamoto, M. Lagrange, and S. Takamichi, “Foley sound synthesis at the dcase 2023 challenge,” in
2023
Earlier work this paper cites.
H. Liu, Z. Chen, Y. Yuan, X. Mei, X. Liu, D. Mandic, W. Wang, and M. D. Plumbley, “AudioLDM: Text-to-audio generation with latent diffusion models,”
Original
2023
Earlier work this paper cites.
M. Tailleur, J. Lee, M. Lagrange, K. Choi, L. M. Heller, K. Imoto, and Y. Okamoto, “Correlation of fréchet audio distance with human perception of environmental audio is embedding dependent,” in
2024
Earlier work this paper cites.
X. ZhiDong, L. XinYu, L. HaiCheng, Z. XiaoYan, and S. Yu, “Sound scene synthesis with audioldm and tango2 for dcase 2024 task7,” Samsung Research China-Nanjing, Nanjing, China, Tech. Rep., July 2024
2024
Earlier work this paper cites.
H. C. Chung and J. H. Jung, “Sound scene synthesis based on gan using contrastive learning and effective time-frequency swap cross attention mechanism,” KT Corporation, Seoul, Republic of Korea, Tech. Rep., July 2024
2024
Earlier work this paper cites.
Y. Yuan, H. Liu, X. Liu, M. D. Plumbley, and W. Wang, “Diffusion based sound scene synthesis for dcase challenge 2024 task 7,” University of Surrey, Guildford, United Kingdom, Tech. Rep., July 2024
2024
Earlier work this paper cites.
S. Ghosh, G. Verma, S. N. Shakya, S. Sharma, and S. Singh, “Sound scene synthesis based on fine-tuned latent diffusion model for dcase challenge 2024 task 7,” Indian Institute of Technology Mandi, Kamand, Mandi, India, Tech. Rep., July 2024
2024
Earlier work this paper cites.

Similar

J. Lee, M. Tailleur, L. M. Heller, K. Choi, M. Lagrange, B. McFee, K. Imoto, and Y. Okamoto, “Challenge on sound scene synthesis: Evaluating text-to-audio generation,” in
2024
Cited alongside, same era.
Y. Chung, J. Lee, and J. Nam, “T-foley: A controllable waveform-domain diffusion model for temporal-event-guided foley sound synthesis,” in
2024
Cited alongside, same era.
M. F. Colombo, F. Ronchini, L. Comanducci, and F. Antonacci, “Mambafoley: Foley sound generation using selective state-space models,”
Original
2024
Cited alongside, same era.
Z. Guo, J. Mao, R. Tao, L. Yan, K. Ouchi, H. Liu, and X. Wang, “Audio generation with multiple conditional diffusion model,” in
2024
Cited alongside, same era.
Z. Xie, X. Xu, Z. Wu, and M. Wu, “Picoaudio: Enabling precise timestamp and frequency controllability of audio events in text-to-audio generation,”

Then

Z. Xie, S. Yu, Q. He, and M. Li, “Sonicvisionlm: Playing sound with vision language models,” in
2024
Later among the works it cites.
J. Lee, J. Im, D. Kim, and J. Nam, “Video-foley: Two-stage video-to-sound generation via temporal event condition for foley sound,”
Original
2024
Later among the works it cites.
Y. Jeong, Y. Kim, S. Chun, and J. Lee, “Read, watch and scream! sound generation from text and video,”
Original
2024
Later among the works it cites.
A. Polyak, A. Zohar, A. Brown, A. Tjandra, A. Sinha, A. Lee, A. Vyas, B. Shi, C.-Y. Ma, C.-Y. Chuang,
Original
2024
Later among the works it cites.
Z. Chen, P. Seetharaman, B. Russell, O. Nieto, D. Bourgin, A. Owens, and J. Salamon, “Video-guided foley sound generation with multimodal controls,”
Original

Beyond the bibliography

alphaXiv searches the wider corpus for related work and actual follow-ups.

Open on alphaXiv

alphaXiv is searching for related work…

Original

2024

Cited alongside, same era.

H. Liu, Y. Yuan, X. Liu, X. Mei, Q. Kong, Q. Tian, Y. Wang, W. Wang, Y. Wang, and M. D. Plumbley, “Audioldm 2: Learning holistic audio generation with self-supervised pretraining,”

2024

Cited alongside, same era.

J. Xue, Y. Deng, Y. Gao, and Y. Li, “Auffusion: Leveraging the power of diffusion and large language models for text-to-audio generation,”

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2024

Cited alongside, same era.

J. Hai, Y. Xu, H. Zhang, C. Li, H. Wang, M. Elhilali, and D. Yu, “Ezaudio: Enhancing text-to-audio generation with efficient diffusion transformer,”

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2024

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Anonymous, “Fugatto 1: Foundational generative audio transformer opus 1,” in

2024

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Z. Evans, J. D. Parker, C. Carr, Z. Zukowski, J. Taylor, and J. Pons, “Stable audio open,”

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2024

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Z. Kong, S.-g. Lee, D. Ghosal, N. Majumder, A. Mehrish, R. Valle, S. Poria, and B. Catanzaro, “Improving text-to-audio models with synthetic captions,”

Original

2024

Cited alongside, same era.

M. Comunità, R. F. Gramaccioni, E. Postolache, E. Rodolà, D. Comminiello, and J. D. Reiss, “Syncfusion: Multimodal onset-synchronized video-to-audio foley synthesis,” in

2024

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2024

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S. S. Kushwaha and Y. Tian, “Vintage: Joint video and text conditioning for holistic audio generation,”

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2024

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Y. Wang, W. Guo, R. Huang, J. Huang, Z. Wang, F. You, R. Li, and Z. Zhao, “Frieren: Efficient video-to-audio generation with rectified flow matching,”

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2024

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