Audio Visual Speech Recognition

视听语音识别

• 批准号: LP0562101
• 负责人: Em/Prof Sridha Sridharan
• 金额: $ 16.29万
• 依托单位: Queensland University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: Linkage Projects
• 财政年份: 2005
• 资助国家: 澳大利亚
• 起止时间: 2005-11-01 至 2009-08-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LP0562101
• 关键词: Audio; Visual; Speech; Recognition

Even though significant advances have been made in automatic speech recognition using acoustic information, the recognition accuracies are still poor in noisy and hostile environments such as in crowds, traffic, factory floors etc. In many of these applications visual information is or can easily be made available in addition to the audio. The aim of this project is to achieve an order of magnitude improvement in speech recognition accuracies in adverse environments by joint processing and modelling of the acoustic modality with visual information in the form of lip shapes and movements. The outcomes will be useful in human computer interaction in adverse environments as well as in the transcription and mining of multimedia data.

尽管在使用声学信息的自动语音识别方面已经取得了重大进展，但在诸如人群、交通、工厂车间等嘈杂和恶劣的环境中，识别的准确性仍然很差。在许多这些应用中，除了音频之外，还可以或可以容易地获得视觉信息。该项目的目的是通过联合处理声学模式和嘴唇形状和运动形式的视觉信息，在恶劣环境中实现语音识别准确率的数量级改进。研究结果将有助于恶劣环境中的人机交互以及多媒体数据的转录和挖掘。