AudioGPT: Understanding and Generating Speech, Music, Sound, and Talking Head - Summary
The paper proposes a multi-modal AI system named AudioGPT that complements Large Language Models (LLMs) with foundation models to process complex audio information and solve numerous understanding and generation tasks. AudioGPT is connected with an input/output interface (ASR, TTS) to support spoke
Arxiv URL: https://arxiv.org/abs/2304.12995v1
Authors: Rongjie Huang, Mingze Li, Dongchao Yang, Jiatong Shi, Xuankai Chang, Zhenhui Ye, Yuning Wu, Zhiqing Hong, Jiawei Huang, Jinglin Liu, Yi Ren, Zhou Zhao, Shinji Watanabe
Summary:
The paper proposes a multi-modal AI system named AudioGPT that complements Large Language Models (LLMs) with foundation models to process complex audio information and solve numerous understanding and generation tasks. AudioGPT is connected with an input/output interface (ASR, TTS) to support spoken dialogue. The paper outlines the principles and processes to evaluate multi-modal LLMs and tests AudioGPT in terms of consistency, capability, and robustness. Experimental results demonstrate the capabilities of AudioGPT in solving AI tasks with speech, music, sound, and talking head understanding and generation in multi-round dialogues.
Key Insights & Learnings:
- AudioGPT complements LLMs with foundation models to process complex audio information and solve numerous understanding and generation tasks.
- AudioGPT is connected with an input/output interface (ASR, TTS) to support spoken dialogue.
- The paper outlines the principles and processes to evaluate multi-modal LLMs and tests AudioGPT in terms of consistency, capability, and robustness.
- AudioGPT is capable of solving AI tasks with speech, music, sound, and talking head understanding and generation in multi-round dialogues.
- LLMs have demonstrated remarkable abilities for tasks such as machine translation, open-ended dialogue modeling, and even code completion.
Terms Mentioned: AudioGPT, Large Language Models, LLMs, ASR, TTS, speech, music, sound, talking head, natural language processing, machine translation, open-ended dialogue modeling, code completion, self-supervised learning, SSL, vector quantization, VQ, autoregressive Transformer, discrete VQ-VAE representations, generative spoken dialogue language model
Technologies / Libraries Mentioned: GitHub
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