Zobrazeno 1 - 10
of 19
pro vyhledávání: '"Li, Jinyu"'
Autor:
Wu, Jian, Gaur, Yashesh, Chen, Zhuo, Zhou, Long, Zhu, Yimeng, Wang, Tianrui, Li, Jinyu, Liu, Shujie, Ren, Bo, Liu, Linquan, Wu, Yu
Large language models (LLMs) have achieved remarkable success in the field of natural language processing, enabling better human-computer interaction using natural language. However, the seamless integration of speech signals into LLMs has not been e
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::99eb9d516394e3811b6f509b7c7fc3d0
http://arxiv.org/abs/2307.03917
http://arxiv.org/abs/2307.03917
Autor:
Yang, Muqiao, Kanda, Naoyuki, Wang, Xiaofei, Wu, Jian, Sivasankaran, Sunit, Chen, Zhuo, Li, Jinyu, Yoshioka, Takuya
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Multi-talker automatic speech recognition (ASR) has been studied to generate transcriptions of natural conversation including overlapping speech of multiple speakers. Due to the difficulty in acquiring real conversation data with high-quality human t
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
We previously proposed contextual spelling correction (CSC) to correct the output of end-to-end (E2E) automatic speech recognition (ASR) models with contextual information such as name, place, etc. Although CSC has achieved reasonable improvement in
Autor:
Wei, Kun, Zhou, Long, Zhang, Ziqiang, Chen, Liping, Liu, Shujie, He, Lei, Li, Jinyu, Wei, Furu
Publikováno v:
ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
Direct speech-to-speech translation (S2ST) is an attractive research topic with many advantages compared to cascaded S2ST. However, direct S2ST suffers from the data scarcity problem because the corpora from speech of the source language to speech of
Autor:
Wang, Tianrui, Zhou, Long, Zhang, Ziqiang, Wu, Yu, Liu, Shujie, Gaur, Yashesh, Chen, Zhuo, Li, Jinyu, Wei, Furu
Recent research shows a big convergence in model architecture, training objectives, and inference methods across various tasks for different modalities. In this paper, we propose VioLA, a single auto-regressive Transformer decoder-only network that u
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::071e31d93750cf76e2c5f8f576a56722
http://arxiv.org/abs/2305.16107
http://arxiv.org/abs/2305.16107
Autor:
Wang, Chengyi, Chen, Sanyuan, Wu, Yu, Zhang, Ziqiang, Zhou, Long, Liu, Shujie, Chen, Zhuo, Liu, Yanqing, Wang, Huaming, Li, Jinyu, He, Lei, Zhao, Sheng, Wei, Furu
We introduce a language modeling approach for text to speech synthesis (TTS). Specifically, we train a neural codec language model (called Vall-E) using discrete codes derived from an off-the-shelf neural audio codec model, and regard TTS as a condit
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::d7122f1b2f27efd14eece69f9f82e478
In real-world applications, users often require both translations and transcriptions of speech to enhance their comprehension, particularly in streaming scenarios where incremental generation is necessary. This paper introduces a streaming Transforme
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::97f88fbd214361d264329b545e34862f
Autor:
Zhang, Ziqiang, Zhou, Long, Wang, Chengyi, Chen, Sanyuan, Wu, Yu, Liu, Shujie, Chen, Zhuo, Liu, Yanqing, Wang, Huaming, Li, Jinyu, He, Lei, Zhao, Sheng, Wei, Furu
We propose a cross-lingual neural codec language model, VALL-E X, for cross-lingual speech synthesis. Specifically, we extend VALL-E and train a multi-lingual conditional codec language model to predict the acoustic token sequences of the target lang
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4332efdacb44ce5ea14a0c5016fb69e1
Autor:
Wang, Peidong, Sun, Eric, Xue, Jian, Wu, Yu, Zhou, Long, Gaur, Yashesh, Liu, Shujie, Li, Jinyu
Automatic speech recognition (ASR) and speech translation (ST) can both use neural transducers as the model structure. It is thus possible to use a single transducer model to perform both tasks. In real-world applications, such joint ASR and ST model
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::baee0aee263ba5ee17798574a87daca5
Masked language model (MLM) has been widely used for understanding tasks, e.g. BERT. Recently, MLM has also been used for generation tasks. The most popular one in speech is using Mask-CTC for non-autoregressive speech recognition. In this paper, we
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::14a1b9148c7a7678b5a4b8df4f8fac75