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of 5 087
pro vyhledávání: '"Yang,Yifan"'
Autor:
Chen, Wenxi, Ma, Ziyang, Yan, Ruiqi, Liang, Yuzhe, Li, Xiquan, Xu, Ruiyang, Niu, Zhikang, Zhu, Yanqiao, Yang, Yifan, Liu, Zhanxun, Yu, Kai, Hu, Yuxuan, Li, Jinyu, Lu, Yan, Liu, Shujie, Chen, Xie
Recent advancements highlight the potential of end-to-end real-time spoken dialogue systems, showcasing their low latency and high quality. In this paper, we introduce SLAM-Omni, a timbre-controllable, end-to-end voice interaction system with single-
Externí odkaz:
http://arxiv.org/abs/2412.15649
Autor:
Yang, Yifan, Ma, Ziyang, Liu, Shujie, Li, Jinyu, Wang, Hui, Meng, Lingwei, Sun, Haiyang, Liang, Yuzhe, Xu, Ruiyang, Hu, Yuxuan, Lu, Yan, Zhao, Rui, Chen, Xie
This paper introduces Interleaved Speech-Text Language Model (IST-LM) for streaming zero-shot Text-to-Speech (TTS). Unlike many previous approaches, IST-LM is directly trained on interleaved sequences of text and speech tokens with a fixed ratio, eli
Externí odkaz:
http://arxiv.org/abs/2412.16102
In 3D understanding, point transformers have yielded significant advances in broadening the receptive field. However, further enhancement of the receptive field is hindered by the constraints of grouping attention. The proxy-based model, as a hot top
Externí odkaz:
http://arxiv.org/abs/2412.11540
Autor:
Zhang, Miaosen, Dai, Qi, Yang, Yifan, Bao, Jianmin, Chen, Dongdong, Qiu, Kai, Luo, Chong, Geng, Xin, Guo, Baining
LMMs have shown impressive visual understanding capabilities, with the potential to be applied in agents, which demand strong reasoning and planning abilities. Nevertheless, existing benchmarks mostly assess their reasoning abilities in language part
Externí odkaz:
http://arxiv.org/abs/2412.04531
Large Language Models (LLMs) have showcased exceptional performance across diverse NLP tasks, and their integration with speech encoder is rapidly emerging as a dominant trend in the Automatic Speech Recognition (ASR) field. Previous works mainly con
Externí odkaz:
http://arxiv.org/abs/2412.00721
Typical dynamic ST data includes trajectory data (representing individual-level mobility) and traffic state data (representing population-level mobility). Traditional studies often treat trajectory and traffic state data as distinct, independent moda
Externí odkaz:
http://arxiv.org/abs/2412.00953
Autor:
BESIII Collaboration, Ablikim, M., Achasov, M. N., Adlarson, P., Ai, X. C., Aliberti, R., Amoroso, A., An, M. R., An, Q., Bai, Y., Bakina, O., Balossino, I., Ban, Y., Batozskaya, V., Begzsuren, K., Berger, N., Berlowski, M., Bertani, M., Bettoni, D., Bianchi, F., Bianco, E., Bortone, A., Boyko, I., Briere, R. A., Brueggemann, A., Cai, H., Cai, X., Calcaterra, A., Cao, G. F., Cao, N., Cetin, S. A., Chang, J. F., Chang, T. T., Chang, W. L., Che, G. R., Chelkov, G., Chen, C., Chen, Chao, Chen, G., Chen, H. S., Chen, M. L., Chen, S. J., Chen, S. M., Chen, T., Chen, X. R., Chen, X. T., Chen, Y. B., Chen, Y. Q., Chen, Z. J., Cheng, W. S., Choi, S. K., Chu, X., Cibinetto, G., Coen, S. C., Cossio, F., Cui, J. J., Dai, H. L., Dai, J. P., Dbeyssi, A., de Boer, R. E., Dedovich, D., Deng, Z. Y., Denig, A., Denysenko, I., Destefanis, M., De Mori, F., Ding, B., Ding, X. X., Ding, Y., Dong, J., Dong, L. Y., Dong, M. Y., Dong, X., Du, M. C., Du, S. X., Duan, Z. H., Egorov, P., Fan, Y. H. Y., Fan, Y. L., Fang, J., Fang, S. S., Fang, W. X., Fang, Y., Farinelli, R., Fava, L., Feldbauer, F., Felici, G., Feng, C. Q., Feng, J. H., Fischer, K, Fritsch, M., Fritzsch, C., Fu, C. D., Fu, J. L., Fu, Y. W., Gao, H., Gao, Y. N., Gao, Yang, Garbolino, S., Garzia, I., Ge, P. T., Ge, Z. W., Geng, C., Gersabeck, E. M., Gilman, A, Goetzen, K., Gong, L., Gong, W. X., Gradl, W., Gramigna, S., Greco, M., Gu, M. H., Guan, C. Y, Guan, Z. L., Guo, A. Q., Guo, L. B., Guo, M. J., Guo, R. P., Guo, Y. P., Guskov, A., Han, T. T., Han, W. Y., Hao, X. Q., Harris, F. A., He, K. K., He, K. L., Heinsius, F. H H., Heinz, C. H., Heng, Y. K., Herold, C., Holtmann, T., Hong, P. C., Hou, G. Y., Hou, X. T., Hou, Y. R., Hou, Z. L., Hu, H. M., Hu, J. F., Hu, T., Hu, Y., Huang, G. S., Huang, K. X., Huang, L. Q., Huang, X. T., Huang, Y. P., Hussain, T., Hüsken, N, Imoehl, W., Jackson, J., Jaeger, S., Janchiv, S., Jeong, J. H., Ji, Q., Ji, Q. P., Ji, X. B., Ji, X. L., Ji, Y. Y., Jia, X. Q., Jia, Z. K., Jiang, H. J., Jiang, P. C., Jiang, S. S., Jiang, T. J., Jiang, X. S., Jiang, Y., Jiao, J. B., Jiao, Z., Jin, S., Jin, Y., Jing, M. Q., Johansson, T., K., X., Kabana, S., Kalantar-Nayestanaki, N., Kang, X. L., Kang, X. S., Kavatsyuk, M., Ke, B. C., Khoukaz, A., Kiuchi, R., Kliemt, R., Kolcu, O. B., Kopf, B., Kuessner, M., Kupsc, A., Kühn, W., Lane, J. J., Larin, P., Lavania, A., Lavezzi, L., Lei, T. T., Lei, Z. H., Leithoff, H., Lellmann, M., Lenz, T., Li, C., Li, C. H., Li, Cheng, Li, D. M., Li, F., Li, G., Li, H., Li, H. B., Li, H. J., Li, H. N., Li, Hui, Li, J. R., Li, J. S., Li, J. W., Li, K. L., Li, Ke, Li, L. J, Li, L. K., Li, Lei, Li, M. H., Li, P. R., Li, Q. X., Li, S. X., Li, T., Li, W. D., Li, W. G., Li, X. H., Li, X. L., Li, Xiaoyu, Li, Y. G., Li, Z. J., Liang, C., Liang, H., Liang, Y. F., Liang, Y. T., Liao, G. R., Liao, L. Z., Liao, Y. P., Libby, J., Limphirat, A., Lin, D. X., Lin, T., Liu, B. J., Liu, B. X., Liu, C., Liu, C. X., Liu, F. H., Liu, Fang, Liu, Feng, Liu, G. M., Liu, H., Liu, H. M., Liu, Huanhuan, Liu, Huihui, Liu, J. B., Liu, J. L., Liu, J. Y., Liu, K., Liu, K. Y., Liu, Ke, Liu, L., Liu, L. C., Liu, Lu, Liu, M. H., Liu, P. L., Liu, Q., Liu, S. B., Liu, T., Liu, W. K., Liu, W. M., Liu, X., Liu, Y., Liu, Y. B., Liu, Z. A., Liu, Z. Q., Lou, X. C., Lu, F. X., Lu, H. J., Lu, J. G., Lu, X. L., Lu, Y., Lu, Y. P., Lu, Z. H., Luo, C. L., Luo, M. X., Luo, T., Luo, X. L., Lyu, X. R., Lyu, Y. F., Ma, F. C., Ma, H. L., Ma, J. L., Ma, L. L., Ma, M. M., Ma, Q. M., Ma, R. Q., Ma, R. T., Ma, X. Y., Ma, Y., Ma, Y. M., Maas, F. E., Maggiora, M., Malde, S., Malik, Q. A., Mangoni, A., Mao, Y. J., Mao, Z. P., Marcello, S., Meng, Z. X., Messchendorp, J. G., Mezzadri, G., Miao, H., Min, T. J., Mitchell, R. E., Mo, X. H., Muchnoi, N. Yu., Muskalla, J., Nefedov, Y., Nerling, F., Nikolaev, I. B., Ning, Z., Nisar, S., Niu, W. D., Niu, Y., Olsen, S. L., Ouyang, Q., Pacetti, S., Pan, X., Pan, Y., Pathak, A., Patteri, P., Pei, Y. P., Pelizaeus, M., Peng, H. P., Peters, K., Ping, J. L., Ping, R. G., Plura, S., Pogodin, S., Prasad, V., Qi, F. Z., Qi, H., Qi, H. R., Qi, M., Qi, T. Y., Qian, S., Qian, W. B., Qiao, C. F., Qin, J. J., Qin, L. Q., Qin, X. P., Qin, X. S., Qin, Z. H., Qiu, J. F., Qu, S. Q., Redmer, C. F., Ren, K. J., Rivetti, A., Rolo, M., Rong, G., Rosner, Ch., Ruan, S. N., Salone, N., Sarantsev, A., Schelhaas, Y., Schoenning, K., Scodeggio, M., Shan, K. Y., Shan, W., Shan, X. Y., Shangguan, J. F., Shao, L. G., Shao, M., Shen, C. P., Shen, H. F., Shen, W. H., Shen, X. Y., Shi, B. A., Shi, H. C., Shi, J. L., Shi, J. Y., Shi, Q. Q., Shi, R. S., Shi, X., Song, J. J., Song, T. Z., Song, W. M., Song, Y. J., Song, Y. X., Sosio, S., Spataro, S., Stieler, F., Su, Y. J., Sun, G. B., Sun, G. X., Sun, H., Sun, H. K., Sun, J. F., Sun, K., Sun, L., Sun, S. S., Sun, T., Sun, W. Y., Sun, Y., Sun, Y. J., Sun, Y. Z., Sun, Z. T., Tan, Y. X., Tang, C. J., Tang, G. Y., Tang, J., Tang, Y. A., Tao, L. Y, Tao, Q. T., Tat, M., Teng, J. X., Thoren, V., Tian, W. H., Tian, Y., Tian, Z. F., Uman, I., Wang, S. J., Wang, B., Wang, B. L., Wang, Bo, Wang, C. W., Wang, D. Y., Wang, F., Wang, H. J., Wang, H. P., Wang, J. P., Wang, K., Wang, L. L., Wang, M., Wang, Meng, Wang, S., Wang, T., Wang, T. J., Wang, W., Wang, W. P., Wang, X., Wang, X. F., Wang, X. J., Wang, X. L., Wang, Y., Wang, Y. D., Wang, Y. F., Wang, Y. H., Wang, Y. N., Wang, Y. Q., Wang, Yaqian, Wang, Yi, Wang, Z., Wang, Z. L., Wang, Z. Y., Wang, Ziyi, Wei, D., Wei, D. H., Weidner, F., Wen, S. P., Wenzel, C. W., Wiedner, U., Wilkinson, G., Wolke, M., Wollenberg, L., Wu, C., Wu, J. F., Wu, L. H., Wu, L. J., Wu, X., Wu, X. H., Wu, Y., Wu, Y. H., Wu, Y. J., Wu, Z., Xia, L., Xian, X. M., Xiang, T., Xiao, D., Xiao, G. Y., Xiao, S. Y., Xiao, Y. L., Xiao, Z. J., Xie, C., Xie, X. H., Xie, Y., Xie, Y. G., Xie, Y. H., Xie, Z. P., Xing, T. Y., Xu, C. F., Xu, C. J., Xu, G. F., Xu, H. Y., Xu, Q. J., Xu, Q. N., Xu, W., Xu, W. L., Xu, X. P., Xu, Y. C., Xu, Z. P., Xu, Z. S., Yan, F., Yan, L., Yan, W. B., Yan, W. C., Yan, X. Q., Yang, H. J., Yang, H. L., Yang, H. X., Yang, Tao, Yang, Y., Yang, Y. F., Yang, Y. X., Yang, Yifan, Yang, Z. W., Yao, Z. P., Ye, M., Ye, M. H., Yin, J. H., You, Z. Y., Yu, B. X., Yu, C. X., Yu, G., Yu, J. S., Yu, T., Yu, X. D., Yuan, C. Z., Yuan, L., Yuan, S. C., Yuan, X. Q., Yuan, Y., Yuan, Z. Y., Yue, C. X., Zafar, A. A., Zeng, F. R., Zeng, X., Zeng, Y., Zeng, Y. J., Zhai, X. Y., Zhai, Y. C., Zhan, Y. H., Zhang, A. Q., Zhang, B. L., Zhang, B. X., Zhang, D. H., Zhang, G. Y., Zhang, H., Zhang, H. H., Zhang, H. Q., Zhang, H. Y., Zhang, J., Zhang, J. J., Zhang, J. L., Zhang, J. Q., Zhang, J. W., Zhang, J. X., Zhang, J. Y., Zhang, J. Z., Zhang, Jianyu, Zhang, Jiawei, Zhang, L. M., Zhang, L. Q., Zhang, Lei, Zhang, P., Zhang, Q. Y., Zhang, Shuihan, Zhang, Shulei, Zhang, X. D., Zhang, X. M., Zhang, X. Y., Zhang, Xuyan, Zhang, Y., Zhang, Y. T., Zhang, Y. H., Zhang, Yan, Zhang, Yao, Zhang, Z. H., Zhang, Z. L., Zhang, Z. Y., Zhao, G., Zhao, J., Zhao, J. Y., Zhao, J. Z., Zhao, Lei, Zhao, Ling, Zhao, M. G., Zhao, S. J., Zhao, Y. B., Zhao, Y. X., Zhao, Z. G., Zhemchugov, A., Zheng, B., Zheng, J. P., Zheng, W. J., Zheng, Y. H., Zhong, B., Zhong, X., Zhou, H., Zhou, L. P., Zhou, X., Zhou, X. K., Zhou, X. R., Zhou, X. Y., Zhou, Y. Z., Zhu, J., Zhu, K., Zhu, K. J., Zhu, L., Zhu, L. X., Zhu, S. H., Zhu, S. Q., Zhu, T. J., Zhu, W. J., Zhu, Y. C., Zhu, Z. A., Zou, J. H., Zu, J.
The inclusive cross sections of prompt $J/\psi$ and $\psi(3686)$ production are measured at center-of-mass energies from 3.808 to 4.951 GeV. The dataset used is 22 fb$^{-1}$ of $e^{+}e^{-}$ annihilation data collected with the BESIII detector operati
Externí odkaz:
http://arxiv.org/abs/2411.19642
Freight truck-related crashes pose significant challenges, leading to substantial economic losses, injuries, and fatalities, with pronounced spatial disparities across different regions. This study adopts a transport geography perspective to examine
Externí odkaz:
http://arxiv.org/abs/2411.17554
Autor:
Yang, Yifan, Zhuo, Jianheng, Jin, Zengrui, Ma, Ziyang, Yang, Xiaoyu, Yao, Zengwei, Guo, Liyong, Kang, Wei, Kuang, Fangjun, Lin, Long, Povey, Daniel, Chen, Xie
Self-supervised learning (SSL) has achieved great success in speech-related tasks, driven by advancements in speech encoder architectures and the expansion of datasets. While Transformer and Conformer architectures have dominated SSL backbones, encod
Externí odkaz:
http://arxiv.org/abs/2411.17100
Autor:
Tian, Rui, Dai, Qi, Bao, Jianmin, Qiu, Kai, Yang, Yifan, Luo, Chong, Wu, Zuxuan, Jiang, Yu-Gang
Commercial video generation models have exhibited realistic, high-fidelity results but are still restricted to limited access. One crucial obstacle for large-scale applications is the expensive training and inference cost. In this paper, we argue tha
Externí odkaz:
http://arxiv.org/abs/2411.13552