Scholarlink

<p>Speech is essential for human communication, but millions of people lose the ability to speak due to conditions such as amyotrophic lateral sclerosis (ALS) or stroke. Assistive technologies like brain-computer interfaces (BCIs), can convert brain signals into speech. However, these technologies still face challenges in decoding accuracy. This issue is especially challenging for tonal languages like Mandarin Chinese. Furthermore, most existing speech datasets are based on Indo-European languages, which hinders our understanding of how tonal information is encoded in the brain. To address this, we introduce a comprehensive open dataset, which includes multimodal signals from 30 subjects using Mandarin Chinese across overt, silent, and imagined speech modes, covering electroencephalogram (EEG), surface electromyogram (sEMG), and speech recordings. This dataset lays a valuable groundwork for exploring the neural encoding of tonal languages, investigating tone-related brain dynamics, and improving assistive communication strategies. It supports cross-linguistic speech processing research and contributes to data-driven neural speech decoding technology innovations.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

An open dataset of multidimensional signals based on different speech patterns in pragmatic Mandarin

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年12月8日

查看全文
  • Ran Zhao,
  • Yanru Bai,
  • Shuming Zhang,
  • Jianing Zhu,
  • Hongxing Liu,
  • Guangjian Ni

摘要

Speech is essential for human communication, but millions of people lose the ability to speak due to conditions such as amyotrophic lateral sclerosis (ALS) or stroke. Assistive technologies like brain-computer interfaces (BCIs), can convert brain signals into speech. However, these technologies still face challenges in decoding accuracy. This issue is especially challenging for tonal languages like Mandarin Chinese. Furthermore, most existing speech datasets are based on Indo-European languages, which hinders our understanding of how tonal information is encoded in the brain. To address this, we introduce a comprehensive open dataset, which includes multimodal signals from 30 subjects using Mandarin Chinese across overt, silent, and imagined speech modes, covering electroencephalogram (EEG), surface electromyogram (sEMG), and speech recordings. This dataset lays a valuable groundwork for exploring the neural encoding of tonal languages, investigating tone-related brain dynamics, and improving assistive communication strategies. It supports cross-linguistic speech processing research and contributes to data-driven neural speech decoding technology innovations.