The impact of vocabulary size and language model order on the polish whispery speech recognition

P. Kozierski, Talar Sadalla, S. Drgas, A. Dabrowski, Joanna Zietkiewicz
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Abstract

The article presents studies on the automatic whispery speech recognition. In the performed research a new corpus with whispery speech has been used. The aim of studies presented in this paper was to check, how the vocabulary size and the language model order influence on the speech recognition quality. It has been concluded that even using recordings with 5,000 different words only it is possible to prepare large vocabulary continuous speech recognition (LVCSR) model. It has been also found that the third order of language model is the best choice. The difference between normal and whispery speech is negligible and is manifested only in higher word error rate index (about 1.5 times higher for whispery speech).
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词汇量和语言模型顺序对波兰语语音识别的影响
本文对自动耳语语音识别进行了研究。在进行的研究中,使用了一个新的语料库,该语料库包含了语音。本文研究的目的是检验词汇量大小和语言模型顺序对语音识别质量的影响。研究表明,即使只使用5000个不同单词的录音,也可以制备大词汇量连续语音识别(LVCSR)模型。研究还发现,三阶语言模型是最佳选择。正常语音与耳语语音的差异可以忽略不计,仅表现为错误率指数较高(耳语语音错误率指数约为1.5倍)。
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