English(EN) Evaluation of forced alignment of code-mixed speech: the case of Hindi-English

新研究详细介绍了改进的印地语-英语代码混合语音强制对齐技术

作者 PulseAugur 编辑部 · [1 个来源] · 2026-07-29 04:00

一篇新研究论文评估了印地语-英语代码混合语音强制对齐的有效性，由于语言变异性，这是一个具有挑战性的领域。研究发现，使用自举策略和在代码混合数据上训练声学模型可显著提高对齐准确性，与单语方法相比，平均错误率降低了十倍。研究结果强调了原则性词典设计和专门训练数据对于可靠的双语语音对齐的必要性。 AI

影响提高了处理多语言输入的语音处理工具的准确性。

排序理由该集群包含一篇发表在arXiv上的学术论文。[lever_c_demoted from research: ic=1 ai=1.0]

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arXiv cs.CL TIER_1 English(EN) · Ayushi Pandey, Pamir Gogoi, Kevin Tang · 2026-07-29 04:00

代码混合语音强制对齐的评估：印地语-英语案例

arXiv:2607.25581v1 Announce Type: new Abstract: Code-mixed speech poses unique challenges to forced alignment: expanded inventories, orthographic errors, and speaker variation. We evaluate forced alignment of Hindi-English code-mixed speech using the Montreal Forced Aligner. We a…