WavSLM simplifies speech generation with distilled WavLM representations

Researchers have developed WavSLM, a novel speech language model that simplifies the generation of coherent speech by distilling self-supervised WavLM representations into a single codebook. This approach allows WavSLM to jointly model semantic and acoustic information within a single token stream, bypassing the need for text supervision or pretraining. Despite its streamlined architecture, WavSLM demonstrates competitive performance on speech generation and consistency benchmarks, utilizing fewer parameters and less training data while enabling streaming inference. AI

RANK_REASON The cluster describes a new research paper detailing a novel speech language model, WavSLM, published on arXiv. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

• alphaXiv
• arXiv
• CatalyzeX
• DagsHub
• Gotit.pub
• Hugging Face
• IArxiv
• Luca Della Libera
• ScienceCast
• WavLM
• WavSLM

• paper
• model release

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →