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Evaluation of the impact in reducing the number of parameters for continuous speech recognition for Brazilian Portuguese

机译:评估减少巴西葡萄牙语连续语音识别参数数量的影响

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With the advent of technology, machines predominate in almost all scenarios of everyday life. The possibility of performing human-machine communication through speech makes this interaction easier and more productive. However, processing requirements still make difficult the implementation of systems for automatic speech recognition on devices with low computational power such as mobile phones, palmtops and appliances. For this purpose, it becomes necessary to research for optimized acoustic and language modeling, associated with use of representative databases, looking for a good compromise between recognition rates and computational demands imposed by embedded systems. The main goal of this work is to model the architecture of a system for continuous speech recognition to Brazilian Portuguese, in order to enable its implementation in an embedded system with limited computing resources.
机译:随着技术的出现,机器几乎在日常生活的所有场景中占主导地位。通过语音执行人机通信的可能性使这种交互变得更容易和更有效率。但是,处理要求仍然使在手机,掌上电脑和家用电器等计算能力较低的设备上实现自动语音识别系统变得困难。为了这个目的,有必要研究与代表性数据库的使用相关联的优化的声学和语言建模,以在识别率和嵌入式系统施加的计算需求之间寻求良好的折衷。这项工作的主要目的是为巴西葡萄牙语连续语音识别系统的体系结构建模,以使其能够在计算资源有限的嵌入式系统中实现。

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