基于Whisper的越南语与英语跨语言音素识别
Whisper based Cross-Lingual Phoneme Recognition between Vietnamese and English
AI总结：
本文针对越南语与英语混合发音的跨语言音素识别难题，提出构建双语音素集并利用PhoWhisper预训练编码器的端到端方法，有效提升了双语语音识别准确率。
摘要：
在混合越南语和英语发音时，跨语言音素识别已成为实现准确自动语音识别（ASR）的重大挑战。与许多语言不同，越南语依赖声调变化来区分词义，而英语的重音模式和非标准发音阻碍了两种语言之间的音素对齐。为应对这一挑战，我们提出了一种新颖的双语语音识别方法，主要贡献有两方面：（1）构建一个具有代表性的双语音素集，弥合越南语与英语音系系统之间的差异；（2）设计一个端到端系统，利用PhoWhisper预训练编码器提取深层高级表征，以提升音素识别性能。大量实验表明，所提方法不仅提高了越南语双语语音识别的准确率，还为应对声调型和重音型音素识别的复杂性提供了一个稳健的框架。
英文摘要：
Cross-lingual phoneme recognition has emerged as a significant challenge for accurate automatic speech recognition (ASR) when mixing Vietnamese and English pronunciations. Unlike many languages, Vietnamese relies on tonal variations to distinguish word meanings, whereas English features stress patterns and non-standard pronunciations that hinder phoneme alignment between the two languages. To address this challenge, we propose a novel bilingual speech recognition approach with two primary contributions: (1) constructing a representative bilingual phoneme set that bridges the differences between Vietnamese and English phonetic systems; (2) designing an end-to-end system that leverages the PhoWhisper pre-trained encoder for deep high-level representations to improve phoneme recognition. Our extensive experiments demonstrate that the proposed approach not only improves recognition accuracy in bilingual speech recognition for Vietnamese but also provides a robust framework for addressing the complexities of tonal and stress-based phoneme recognition
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
