Fetching the paper…
Reading the bibliography…
We introduce the latest progress of Qwen-Audio, a large-scale audio-language model called Qwen2-Audio, which is capable of accepting various audio signal inputs and performing audio analysis or direct textual responses with regard to speech instructions.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
Earlier work this paper cites.
The fisher corpus: A resource for the next generations of speech-to-text
Christopher Cieri, David Miller, and Kevin Walker · 2004
Earlier work this paper cites.
Covost 2: A massively multilingual speech-to-text translation corpus
Changhan Wang, Anne Wu, and Juan Miguel Pino · 2007
Earlier work this paper cites.
Librispeech: An ASR corpus based on public domain audio books
Vassil Panayotov, Guoguo Chen, Daniel Povey, and Sanjeev Khudanpur · 2015
Earlier work this paper cites.
AISHELL-2: transforming mandarin ASR research into industrial scale
Jiayu Du, Xingyu Na, Xuechen Liu, and Hui Bu · 2018
Earlier work this paper cites.
Audiocaps: Generating captions for audios in the wild
Chris Dongjoo Kim, Byeongchang Kim, Hyunmin Lee, and Gunhee Kim · 2019
Earlier work this paper cites.
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
Earlier work this paper cites.
Common voice: A massively-multilingual speech corpus
R. Ardila, M. Branson, K. Davis, M. Henretty, M. Kohler, J. Meyer, R. Morais, L. Saunders, F. M. Tyers, and G. Weber · 2020
Earlier work this paper cites.
Clotho: an audio captioning dataset
Konstantinos Drossos, Samuel Lipping, and Tuomas Virtanen · 2020
Earlier work this paper cites.
Speecht5: Unified-modal encoder-decoder pre-training for spoken language processing
Junyi Ao, Rui Wang, Long Zhou, Chengyi Wang, Shuo Ren, Yu Wu, Shujie Liu, Tom Ko, Qing Li, Yu Zhang, et al · 2021
Earlier work this paper cites.
Speechnet: A universal modularized model for speech processing tasks
Yi-Chen Chen, Po-Han Chi, Shu-wen Yang, Kai-Wei Chang, Jheng-hao Lin, Sung-Feng Huang, Da-Rong Liu, Chi-Liang Liu, Cheng-Kuang Lee, and Hung-yi Lee · 2021
Earlier work this paper cites.
Wavlm: Large-scale self-supervised pre-training for full stack speech processing
Sanyuan Chen, Chengyi Wang, Zhengyang Chen, Yu Wu, Shujie Liu, Zhuo Chen, Jinyu Li, Naoyuki Kanda, Takuya Yoshioka, Xiong Xiao, Jian Wu, Long Zhou, Shuo Ren, Yanmin Qian, Yao Qian, Jian Wu, Michael Zeng, Xiangzhan Yu, and Furu Wei · 2022
Earlier work this paper cites.
Fleurs: Few-shot learning evaluation of universal representations of speech
Alexis Conneau, Min Ma, Simran Khanuja, Yu Zhang, Vera Axelrod, Siddharth Dalmia, Jason Riesa, Clara Rivera, and Ankur Bapna · 2022
Cited alongside, same era.
CLAP: learning audio concepts from natural language supervision
Benjamin Elizalde, Soham Deshmukh, Mahmoud Al Ismail, and Huaming Wang · 2022
Cited alongside, same era.
Vocalsound: A dataset for improving human vocal sounds recognition
Yuan Gong, Jin Yu, and James R. Glass · 2022
Cited alongside, same era.
Mmspeech: Multi-modal multi-task encoder-decoder pre-training for speech recognition
Xiaohuan Zhou, Jiaming Wang, Zeyu Cui, Shiliang Zhang, Zhijie Yan, Jingren Zhou, and Chang Zhou · 2022
Cited alongside, same era.
Musiclm: Generating music from text
Andrea Agostinelli, Timo I Denk, Zalán Borsos, Jesse Engel, Mauro Verzetti, Antoine Caillon, Qingqing Huang, Aren Jansen, Adam Roberts, Marco Tagliasacchi, et al · 2023
Robust speech recognition via large-scale weak supervision
Alec Radford, Jong Wook Kim, Tao Xu, Greg Brockman, Christine McLeavey, and Ilya Sutskever · 2023
Later among the works it cites.
Spokenwoz: A large-scale speech-text benchmark for spoken task-oriented dialogue in multiple domains
Shuzheng Si, Wentao Ma, Yuchuan Wu, Yinpei Dai, Haoyu Gao, Ting-En Lin, Hangyu Li, Rui Yan, Fei Huang, and Yongbin Li · 2023
Later among the works it cites.
Pandagpt: One model to instruction-follow them all
Yixuan Su, Tian Lan, Huayang Li, Jialu Xu, Yan Wang, and Deng Cai · 2023
Later among the works it cites.
Speechgpt: Empowering large language models with intrinsic cross-modal conversational abilities
Dong Zhang, Shimin Li, Xin Zhang, Jun Zhan, Pengyu Wang, Yaqian Zhou, and Xipeng Qiu · 2023
Later among the works it cites.
Speechverse: A large-scale generalizable audio language model
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Cited alongside, same era.
Jinze Bai, Shuai Bai, Yunfei Chu, Zeyu Cui, Kai Dang, Xiaodong Deng, Yang Fan, Wenbin Ge, Yu Han, Fei Huang, et al · 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
Cited alongside, same era.
Pengi: An audio language model for audio tasks
Soham Deshmukh, Benjamin Elizalde, Rita Singh, and Huaming Wang · 2023
Cited alongside, same era.
Funasr: A fundamental end-to-end speech recognition toolkit
Zhifu Gao, Zerui Li, Jiaming Wang, Haoneng Luo, Xian Shi, Mengzhe Chen, Yabin Li, Lingyun Zuo, Zhihao Du, Zhangyu Xiao, and Shiliang Zhang · 2023
Cited alongside, same era.
Macaw-llm: Multi-modal language modeling with image, audio, video, and text integration
Chenyang Lyu, Minghao Wu, Longyue Wang, Xinting Huang, Bingshuai Liu, Zefeng Du, Shuming Shi, and Zhaopeng Tu · 2023
Cited alongside, same era.
Gpt-4 technical report, 2023
OpenAI · 2023
Cited alongside, same era.
Introducing qwen-7b: Open foundation and human-aligned models (of the state-of-the-arts), 2023
Qwen · 2023
Cited alongside, same era.
Nilaksh Das, Saket Dingliwal, Srikanth Ronanki, Rohit Paturi, David Huang, Prashant Mathur, Jie Yuan, Dhanush Bekal, Xing Niu, Sai Muralidhar Jayanthi, et al · 2024
Closest in time.
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
Closest in time.
Gpt-4o, 2024
OpenAI · 2024
Closest in time.
Direct preference optimization: Your language model is secretly a reward model
Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D Manning, Stefano Ermon, and Chelsea Finn · 2024
Closest in time.
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Machel Reid, Nikolay Savinov, Denis Teplyashin, Dmitry Lepikhin, Timothy Lillicrap, Jean-baptiste Alayrac, Radu Soricut, Angeliki Lazaridou, Orhan Firat, Julian Schrittwieser, et al · 2024
Closest in time.
SALMONN: Towards generic hearing abilities for large language models
Changli Tang, Wenyi Yu, Guangzhi Sun, Xianzhao Chen, Tian Tan, Wei Li, Lu Lu, Zejun MA, and Chao Zhang · 2024
Closest in time.
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 · 2024
Closest in time.