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News/Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks
arxiv
PublishedApril 24, 2026 at 4:00 AM
▲bullish

Basic syntax from speech: Spontaneous concatenation in unsupervised deep neural networks

Source
arxiv.orgfull article ↗
Read on arxiv→
Publisher summary· verbatim

arXiv:2305.01626v4 Announce Type: replace-cross Abstract: Computational models of syntax are predominantly text-based. Here we propose that the most basic first step in the evolution of syntax can be modeled directly from raw speech in a fully unsupervised way. We focus on one of the most ubiquitous

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Discussion
Mentioned models
03
  • 01
    ciwGAN
  • 02
    fiwGAN
  • 03
    CNN
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#speech-processing#neural-networks#language-modeling#compositionality

No replies yet. Be first.

Mentioned models
03
  • 01
    ciwGAN
  • 02
    fiwGAN
  • 03
    CNN
Source
↗
arxiv
Read original ↗All from arxiv →
Tags
04
#speech-processing#neural-networks#language-modeling#compositionality

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arxivSFMambaNet: Spectral-Frequency Enhanced Selective State Space Model for Correspondence Pruning17h
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Originally published on arxiv ↗
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