Abstract In this paper the improvement in performance of automatic speech recognition (ASR) system is achieved with help of pitch dependent features and probability of voicing estimated features. The pitch dependent features are useful for tonal language ASR system. Punjabi language is highly tonal language and hence here we are building ASR system for Punjabi language with pitch dependent features and probability of voicing estimated features. The word error rate of system gives the performance of system which drastically improves with pitch dependent features and probability of voicing estimated features. Comparison of Yin, SAcC, Fundamental Frequency Variation (FFV) and Kaldi pitch features of ASR system were done in terms of WER. The KALDI pitch tracker of Kaldi toolkit gives the best performance ASR system among other featured ASR systems. The performance of ASR system is evaluated for Punjabi language.

中文翻译：

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KALDI 工具包上旁遮普语具有音调相关特征的自动语音识别系统

摘要 在本文中，自动语音识别 (ASR) 系统的性能改进是通过依赖于音高的特征和发声概率估计特征来实现的。音高相关特征对于声调语言 ASR 系统很有用。旁遮普语是高度音调的语言，因此在这里我们正在为旁遮普语构建 ASR 系统，该系统具有音高相关特征和发音估计特征的概率。系统的单词错误率给出了系统的性能，该性能随着音调相关特征和发音估计特征的概率而显着提高。ASR 系统的音、SAcC、基频变化 (FFV) 和 Kaldi 音高特征的比较是根据 WER 进行的。Kaldi 工具包中的 KALDI 音高跟踪器在其他特色 ASR 系统中提供了最佳性能的 ASR 系统。