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Influence of Lombard Effect: Accuracy Analysis of Simulation-Based Assessments of Noisy Speech Recognition Systems for Various Recognition Conditions

机译:伦巴德效应的影响:噪声识别系统在各种识别条件下基于仿真评估的准确性分析

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The accuracy of simulation-based assessments of speech recognition systems under noisy conditions is investigated with a focus on the influence of me Lombard effect on the speech recognition performances. This investigation was carried out under various recognition conditions of different sound pressure levels of ambient noise, for different recognition tasks, such as continuous speech recognition and spoken word recognition, and using different recognition systems, i.e., systems with and without adaptation of the accustic models to ambient noise. Experimental results showed that accurate simulation was not always achieved when dry sources with neutral talking style were used, but it could be achieved if the dry sources that include the influence of the Lombard effect were used; the simulation in the latter case is accurate, irrespective of the recognition conditions.
机译:研究了在嘈杂条件下基于仿真的语音识别系统评估的准确性,重点是伦巴特效应对语音识别性能的影响。这项研究是在环境噪声的声压级不同的各种识别条件下,针对不同的识别任务(例如连续语音识别和口头单词识别),并使用不同的识别系统(即具有和不具有自适应模型的系统)进行的对环境的噪音。实验结果表明,当使用具有中性说话风格的干燥声源时,并非总是能获得准确的模拟,但如果使用包含伦巴底效应的干燥声源,则可以实现准确的模拟。不论识别条件如何,后一种情况下的模拟都是准确的。

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