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We introduce AudioBench, a universal benchmark designed to evaluate Audio Large Language Models (AudioLLMs).
Hellaswag: Can a machine really finish your sentence?
Rowan Zellers, Ari Holtzman, Yonatan Bisk, Ali Farhadi, and Yejin Choi. 2019 · 1905
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AIR-bench: Benchmarking large audio-language models via generative comprehension
Qian Yang, Jin Xu, Wenrui Liu, Yunfei Chu, Ziyue Jiang, Xiaohuan Zhou, Yichong Leng, Yuanjun Lv, Zhou Zhao, Chang Zhou, and Jingren Zhou. 2024a · 1998
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Meteor: An automatic metric for mt evaluation with improved correlation with human judgments
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Iemocap: Interactive emotional dyadic motion capture database
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Survey on speech emotion recognition: Features, classification schemes, and databases
Moataz El Ayadi, Mohamed S Kamel, and Fakhri Karray. 2011 · 2011
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Ted-lium: an automatic speech recognition dedicated corpus
Anthony Rousseau, Paul Deléglise, and Yannick Esteve. 2012 · 2012
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Librispeech: an asr corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur. 2015 · 2015
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Voxceleb: a large-scale speaker identification dataset
Arsha Nagrani, Joon Son Chung, and Andrew Zisserman. 2017 · 2017
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Think you have solved question answering? try arc, the ai2 reasoning challenge
Peter Clark, Isaac Cowhey, Oren Etzioni, Tushar Khot, Ashish Sabharwal, Carissa Schoenick, and Oyvind Tafjord. 2018 · 2018
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Audiocaps: Generating captions for audios in the wild
Chris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, and Gunhee Kim. 2019 · 2019
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Ok-vqa: A visual question answering benchmark requiring external knowledge
Kenneth Marino, Mohammad Rastegari, Ali Farhadi, and Roozbeh Mottaghi. 2019 · 2019
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MELD: A multimodal multi-party dataset for emotion recognition in conversations
Soujanya Poria, Devamanyu Hazarika, Navonil Majumder, Gautam Naik, Erik Cambria, and Rada Mihalcea. 2019 · 2019
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Dream: A challenge data set and models for dialogue-based reading comprehension
Kai Sun, Dian Yu, Jianshu Chen, Dong Yu, Yejin Choi, and Claire Cardie. 2019 · 2019
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Common voice: A massively-multilingual speech corpus
Rosana Ardila, Megan Branson, Kelly Davis, Michael Kohler, Josh Meyer, Michael Henretty, Reuben Morais, Lindsay Saunders, Francis Tyers, and Gregor Weber. 2020 · 2020
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On the opportunities and risks of foundation models
Rishi Bommasani, Drew A Hudson, Ehsan Adeli, Russ Altman, Simran Arora, Sydney von Arx, Michael S Bernstein, Jeannette Bohg, Antoine Bosselut, Emma Brunskill, et al. 2021 · 2021
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Gigaspeech: An evolving, multi-domain asr corpus with 10,000 hours of transcribed audio
Guoguo Chen, Shuzhou Chai, Guanbo Wang, Jiayu Du, Wei-Qiang Zhang, Chao Weng, Dan Su, Daniel Povey, Jan Trmal, Junbo Zhang, et al. 2021 · 2021
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Earnings-21: A practical benchmark for asr in the wild
Miguel Del Rio, Natalie Delworth, Ryan Westerman, Michelle Huang, Nishchal Bhandari, Joseph Palakapilly, Quinten McNamara, Joshua Dong, Piotr Zelasko, and Miguel Jetté. 2021 · 2021
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The people’s speech: A large-scale diverse english speech recognition dataset for commercial usage
Daniel Galvez, Greg Diamos, Juan Ciro, Juan Felipe Cerón, Keith Achorn, Anjali Gopi, David Kanter, Maximilian Lam, Mark Mazumder, and Vijay Janapa Reddi. 2021 · 2021
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt. 2021 · 2021
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Next-qa: Next phase of question-answering to explaining temporal actions
Junbin Xiao, Xindi Shang, Angela Yao, and Tat-Seng Chua. 2021 · 2021
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Earnings-22: A practical benchmark for accents in the wild
Miguel Del Rio, Peter Ha, Quinten McNamara, Corey Miller, and Shipra Chandra. 2022 · 2022
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Clotho-aqa: A crowdsourced dataset for audio question answering
Samuel Lipping, Parthasaarathy Sudarsanam, Konstantinos Drossos, and Tuomas Virtanen. 2022 · 2022
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Language models are multilingual chain-of-thought reasoners
Freda Shi, Mirac Suzgun, Markus Freitag, Xuezhi Wang, Suraj Srivats, Soroush Vosoughi, Hyung Won Chung, Yi Tay, Sebastian Ruder, Denny Zhou, et al. 2022 · 2022
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Slue phase-2: A benchmark suite of diverse spoken language understanding tasks
Suwon Shon, Siddhant Arora, Chyi-Jiunn Lin, Ankita Pasad, Felix Wu, Roshan Sharma, Wei-Lun Wu, Hung-Yi Lee, Karen Livescu, and Shinji Watanabe. 2022 · 2022
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Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023
Cited alongside, same era.
VioLA: Unified codec language models for speech recognition, synthesis, and translation
Tianrui Wang, Long Zhou, Ziqiang Zhang, Yu Wu, Shujie Liu, Yashesh Gaur, Zhuo Chen, Jinyu Li, and Furu Wei. 2023 · 2023
Later among the works it cites.
Mm-vet: Evaluating large multimodal models for integrated capabilities
Weihao Yu, Zhengyuan Yang, Linjie Li, Jianfeng Wang, Kevin Lin, Zicheng Liu, Xinchao Wang, and Lijuan Wang. 2023 · 2023
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Mmmu: A massive multi-discipline multimodal understanding and reasoning benchmark for expert agi
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al. 2023 · 2023
Later among the works it cites.
Promptbench: Towards evaluating the robustness of large language models on adversarial prompts
Kaijie Zhu, Jindong Wang, Jiaheng Zhou, Zichen Wang, Hao Chen, Yidong Wang, Linyi Yang, Wei Ye, Neil Zhenqiang Gong, Yue Zhang, et al. 2023 · 2023
Later among the works it cites.
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Kabir Ahuja, Harshita Diddee, Rishav Hada, Millicent Ochieng, Krithika Ramesh, Prachi Jain, Akshay Nambi, Tanuja Ganu, Sameer Segal, Maxamed Axmed, et al. 2023 · 2023
Cited alongside, same era.
Qwen-audio: Advancing universal audio understanding via unified large-scale audio-language models
Yunfei Chu, Jin Xu, Xiaohuan Zhou, Qian Yang, Shiliang Zhang, Zhijie Yan, Chang Zhou, and Jingren Zhou. 2023 · 2023
Cited alongside, same era.
Pengi: An audio language model for audio tasks
Soham Deshmukh, Benjamin Elizalde, Rita Singh, and Huaming Wang. 2023 · 2023
Cited alongside, same era.
Joint audio and speech understanding
Yuan Gong, Alexander H. Liu, Hongyin Luo, Leonid Karlinsky, and James Glass. 2023 · 2023
Cited alongside, same era.
AudioGPT: Understanding and generating speech, music, sound, and talking head
Rongjie Huang, Mingze Li, Dongchao Yang, Jiatong Shi, Xuankai Chang, Zhenhui Ye, Yuning Wu, Zhiqing Hong, Jia-Bin Huang, Jinglin Liu, Yixiang Ren, Zhou Zhao, and Shinji Watanabe. 2023 · 2023
Cited alongside, same era.
Whisper model adaptation for FSR-2023 Hakka speech recognition challenge
Yi-Chin Huang and Ji-Qian Tsai. 2023 · 2023
Cited alongside, same era.
Albert Q Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, et al. 2023 · 2023
Cited alongside, same era.
Mvbench: A comprehensive multi-modal video understanding benchmark
Kunchang Li, Yali Wang, Yinan He, Yizhuo Li, Yi Wang, Yi Liu, Zun Wang, Jilan Xu, Guo Chen, Ping Luo, et al. 2023 · 2023
Cited alongside, same era.
UniverSLU: Universal spoken language understanding for diverse tasks with natural language instructions
Siddhant Arora, Hayato Futami, Jee weon Jung, Yifan Peng, and Yosuke Kashiwagi Roshan Sharma, Emiru Tsunoo, Karen Livescu, and Shinji Watanabe. 2024 · 2024
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Xtts: a massively multilingual zero-shot text-to-speech model
Edresson Casanova, Kelly Davis, Eren Gölge, Görkem Göknar, Iulian Gulea, Logan Hart, Aya Aljafari, Joshua Meyer, Reuben Morais, Samuel Olayemi, and Julian Weber. 2024 · 2024
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Chatbot arena: An open platform for evaluating llms by human preference
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael Jordan, Joseph E Gonzalez, et al. 2024 · 2024
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Yunfei Chu, Jin Xu, Qian Yang, Haojie Wei, Xipin Wei, Zhifang Guo, Yichong Leng, Yuanjun Lv, Jinzheng He, Junyang Lin, et al. 2024 · 2024
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SpeechVerse: A large-scale generalizable audio language model
Nilaksh Das, Saket Dingliwal, S. Ronanki, Rohit Paturi, David Huang, Prashant Mathur, Jie Yuan, Dhanush Bekal, Xing Niu, Sai Muralidhar Jayanthi, Xilai Li, Karel Mundnich, Monica Sunkara, Sundararajan Srinivasan, Kyu J Han, and Katrin Kirchhoff. 2024 · 2024
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Length-controlled alpacaeval: A simple way to debias automatic evaluators
Yann Dubois, Balázs Galambosi, Percy Liang, and Tatsunori B Hashimoto. 2024 · 2024
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Video-mme: The first-ever comprehensive evaluation benchmark of multi-modal llms in video analysis
Chaoyou Fu, Yuhan Dai, Yondong Luo, Lei Li, Shuhuai Ren, Renrui Zhang, Zihan Wang, Chenyu Zhou, Yunhang Shen, Mengdan Zhang, et al. 2024 · 2024
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Dynamic-superb: Towards a dynamic, collaborative, and comprehensive instruction-tuning benchmark for speech
Chien-yu Huang, Ke-Han Lu, Shih-Heng Wang, Chi-Yuan Hsiao, Chun-Yi Kuan, Haibin Wu, Siddhant Arora, Kai-Wei Chang, Jiatong Shi, Yifan Peng, et al. 2024a · 2024
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Prometheus 2: An open source language model specialized in evaluating other language models
Seungone Kim, Juyoung Suk, Shayne Longpre, Bill Yuchen Lin, Jamin Shin, Sean Welleck, Graham Neubig, Moontae Lee, Kyungjae Lee, and Minjoon Seo. 2024 · 2024
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Audio Flamingo: A novel audio language model with few-shot learning and dialogue abilities
Zhifeng Kong, Arushi Goel, Rohan Badlani, Wei Ping, Rafael Valle, and Bryan Catanzaro. 2024 · 2024
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Tempcompass: Do video llms really understand videos?
Yuanxin Liu, Shicheng Li, Yi Liu, Yuxiang Wang, Shuhuai Ren, Lei Li, Sishuo Chen, Xu Sun, and Lu Hou. 2024 · 2024
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Investigating the emergent audio classification ability of asr foundation models
Rao Ma, Adian Liusie, Mark John Francis Gales, and Kate Knill. 2024 · 2024
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Vibe-eval: A hard evaluation suite for measuring progress of multimodal language models
Piotr Padlewski, Max Bain, Matthew Henderson, Zhongkai Zhu, Nishant Relan, Hai Pham, Donovan Ong, Kaloyan Aleksiev, Aitor Ormazabal, Samuel Phua, et al. 2024 · 2024
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SALMONN: Towards generic hearing abilities for large language models
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Seaeval for multilingual foundation models: From cross-lingual alignment to cultural reasoning
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Judging llm-as-a-judge with mt-bench and chatbot arena
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