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English(EN) SpeakPay: Domain-Adaptive LoRA Fine-Tuning of Whisper for Low-Resource Nepali Financial Speech Recognition

Whisper针对尼泊尔金融语音指令进行微调,提升可访问性

研究人员开发了SpeakPay,这是一款语音优先的数字钱包,旨在帮助尼泊尔的视障用户。核心技术贡献是使用LoRA在Whisper large-v2模型上进行域自适应微调。这种微调应用于一个包含403个尼泊尔金融指令的新数据集NepFinSpeech-403,将词错误率从129.95%显著降低到42.58%,并将交易成功率提高了约20倍。研究还发现,仅需100条特定领域的话语就能使错误率减半,而性能在大约300个样本后趋于稳定。 AI

影响 通过改进金融语音指令识别,增强了低资源地区视障用户的可访问性。

排序理由 该集群基于一篇详细介绍新数据集和语音识别微调方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

在 arXiv cs.CL 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

Whisper针对尼泊尔金融语音指令进行微调,提升可访问性

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该集群基于一篇详细介绍新数据集和语音识别微调方法的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]
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报道来源 [1]

  1. arXiv cs.CL TIER_1 English(EN) · Biraj Subedi ·

    SpeakPay:面向低资源尼泊尔语金融语音识别的领域自适应LoRA微调Whisper

    arXiv:2609.01737v1 Announce Type: new Abstract: Mobile payment applications in Nepal are graphically mediated and largely inaccessible to visually impaired users. This paper presents SpeakPay, a voice-first digital wallet, and documents the central technical contribution: a contr…