Summary of Get Large Language Models Ready to Speak: a Late-fusion Approach For Speech Generation, by Maohao Shen et al.
Get Large Language Models Ready to Speak: A Late-fusion Approach for Speech Generation
by Maohao Shen, Shun Zhang, Jilong Wu, Zhiping Xiu, Ehab AlBadawy, Yiting Lu, Mike Seltzer, Qing He
First submitted to arxiv on: 27 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper presents a breakthrough in text-to-speech (TTS) technology using large language models (LLMs). The authors introduce TTS-Llama, a fine-tuned LLM that achieves state-of-the-art performance in speech synthesis. Building on this success, they propose MoLE-Llama, a multimodal LLM that can handle both text and speech inputs. Through empirical results, the paper shows that MoLE-Llama performs competitively on text-only question-answering tasks and TTS tasks, while also mitigating catastrophic forgetting issues in either modality. The authors further demonstrate MoLE-Llama’s potential as a multimodal dialog system capable of generating speech for text-in-speech-out question-answering tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research is about making computers talk like humans. Right now, computers are really good at understanding and processing written text, but they’re not great at speaking. The scientists developed a new way to make computers generate natural-sounding speech using special language models. They tested this approach and found that it worked well for both writing and speaking tasks. This breakthrough has the potential to improve computer systems that can have conversations with humans. |
Keywords
» Artificial intelligence » Llama » Question answering
