巴维埃卡开源语音识别工具包

Daniel Bolaños
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引用次数: 21

摘要

本文介绍了用于语音研究和系统开发的开源语音识别工具包Bavieca的设计。该工具包支持基于格的判别训练、广泛的语音上下文、有效的声学评分、大型n-gram语言模型以及最常见的特征和模型转换。Bavieca完全是用c++编写的,提供了一个简单和模块化的设计,强调可伸缩性和可重用性。巴维埃卡在标准基准测试中取得了具有竞争力的成绩。该工具包在高度不受限制的Apache 2.0许可下发布,并且可以在SourceForge上免费获得。
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The Bavieca open-source speech recognition toolkit
This article describes the design of Bavieca, an open-source speech recognition toolkit intended for speech research and system development. The toolkit supports lattice-based discriminative training, wide phonetic-context, efficient acoustic scoring, large n-gram language models, and the most common feature and model transformations. Bavieca is written entirely in C++ and presents a simple and modular design with an emphasis on scalability and reusability. Bavieca achieves competitive results in standard benchmarks. The toolkit is distributed under the highly unrestricted Apache 2.0 license, and is freely available on SourceForge.
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