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The ASRS_RL - A Research Platform for Spoken Language Recognition and Understanding Experiments

机译:ASRS_RL-口语识别和实验研究平台

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In the present paper are described the component stages implemented on the Automatic Speech Recognition System for Romanian Language, ASRS_RL and the speech recognition experiments made with the system. The discussed stages are the feature extraction based on cepstral analysis and linear prediction and the learning strategies implemented on the system for acoustical modelling. The first goal of our research was to develop and experiment a system for continuous speech recognition and understanding in the statistical framework of hidden Markov models (HMM). A second goal was to asses other learning strategies like support vector machines (SVM), artificial neural networks (ANN), and some hybrid structures as alternatives for the HMM. The made experiments in isolated words (digits) and vowels recognition gave good results and proved the competitively of the applied new structures.
机译:本文介绍了在罗马尼亚语言自动语音识别系统ASRS_RL上实现的组成阶段以及使用该系统进行的语音识别实验。讨论的阶段是基于倒谱分析和线性预测的特征提取以及在声学建模系统上实现的学习策略。我们研究的首要目标是开发和试验一种在隐马尔可夫模型(HMM)的统计框架中进行连续语音识别和理解的系统。第二个目标是评估其他学习策略,例如支持向量机(SVM),人工神经网络(ANN)和一些混合结构,作为HMM的替代方案。在孤立的单词(数字)和元音识别方面进行的实验给出了良好的结果,并证明了所应用新结构的竞争力。

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