嘈杂条件下越南语大词汇量连续语音识别系统的开发

Proceedings of the 9th International Symposium on Information and Communication Technology Pub Date : 2018-12-06 DOI:10.1145/3287921.3287938

Quoc Bao Nguyen, Van Tuan Mai, Quang Trung Le, Ba Quyen Dam, Van Hai Do

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引用次数: 6

摘要

在本文中，我们首先介绍了我们收集500小时越南语阅读语音语料库的工作。然后，应用数据增强、递归神经网络语言模型评分、语言模型自适应、瓶颈特征、系统组合等技术构建语音识别系统。我们的最终系统在有噪声的测试集上实现了6.9%的低单词错误率。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Development of a Vietnamese Large Vocabulary Continuous Speech Recognition System under Noisy Conditions

In this paper, we first present our effort to collect a 500-hour corpus for Vietnamese read speech. After that, various techniques such as data augmentation, recurrent neural network language model rescoring, language model adaptation, bottleneck feature, system combination are applied to build the speech recognition system. Our final system achieves a low word error rate at 6.9% on the noisy test set.

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Proceedings of the 9th International Symposium on Information and Communication Technology

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