Towards audio language modeling -- an overview
Fuente:
arXiv
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| Autori principali: | , , , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2024
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| Soggetti: | |
| Accesso online: | |
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| _version_ | 1866929249162625024 |
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| author | Wu, Haibin Chen, Xuanjun Lin, Yi-Cheng Chang, Kai-wei Chung, Ho-Lam Liu, Alexander H. Lee, Hung-yi |
| author_facet | Wu, Haibin Chen, Xuanjun Lin, Yi-Cheng Chang, Kai-wei Chung, Ho-Lam Liu, Alexander H. Lee, Hung-yi |
| contents | Neural audio codecs are initially introduced to compress audio data into compact codes to reduce transmission latency. Researchers recently discovered the potential of codecs as suitable tokenizers for converting continuous audio into discrete codes, which can be employed to develop audio language models (LMs). Numerous high-performance neural audio codecs and codec-based LMs have been developed. The paper aims to provide a thorough and systematic overview of the neural audio codec models and codec-based LMs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2402_13236 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Towards audio language modeling -- an overview Wu, Haibin Chen, Xuanjun Lin, Yi-Cheng Chang, Kai-wei Chung, Ho-Lam Liu, Alexander H. Lee, Hung-yi Audio and Speech Processing Sound Neural audio codecs are initially introduced to compress audio data into compact codes to reduce transmission latency. Researchers recently discovered the potential of codecs as suitable tokenizers for converting continuous audio into discrete codes, which can be employed to develop audio language models (LMs). Numerous high-performance neural audio codecs and codec-based LMs have been developed. The paper aims to provide a thorough and systematic overview of the neural audio codec models and codec-based LMs. |
| title | Towards audio language modeling -- an overview |
| topic | Audio and Speech Processing Sound |
| url | https://arxiv.org/abs/2402.13236 |