A comparison of HTK, ISIP and julius in slovenian large vocabulary continuous speech recognition
A comparison of HTK, ISIP and julius in slovenian large vocabulary continuous speech recognition
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HTK、ISIP 和 julius 在斯洛文尼亚语大词汇量连续语音识别中的比较
DOI：
10.21437/icslp.2002-227
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发表时间：
2002
期刊：
影响因子：
--
通讯作者：
Z. Kacic
中科院分区：
文献类型：
--
作者：
T. Rotovnik;M. Maučec;B. Horvat;Z. Kacic
在本文中，介绍了不同语音解码器的识别，以实现斯洛文尼亚大型词汇识别任务。为了进行语音识别，使用了两种不同类型的词典和语言模型。基于单词的模型用于基线系统和子字（词干和末端）模型进行比较。对于所有解码器，都使用了两通解码策略。在所有三个解码器的情况下，使用Stem-Eddend模型（平均3％的绝对值）实现了更好的识别结果。实验还显示出与朱利叶斯（Julius）解码器相比而不是另外两个解码器的识别结果稍好，而实时因子的提高为65％。
In this paper recognition results from different speech decoders are presented for Slovenian large vocabulary speech recognition task. For speech recognition two different types of lexica and language models were used. Word based models were used for baseline system and sub-word (stems and endings) based models for comparison. For all decoders a two-pass decoding strategy was used. With all three decoders better recognition results were achieved using stem-ending models (3% absolute on average). Experiments also showed slightly better recognition results with Julius decoder, as opposed to two other decoders, and improvement of real-time factor for 65%.