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在基于语音的子单元建模的转录的研究进展,对齐和手语识别

Advances in Phonetics-based Sub-Unit Modeling for Transcription, Alignment and Sign Language Recognition
课程网址: http://videolectures.net/gesturerecognition2011_vogler_advances/  
主讲教师: Christian Vogler
开课单位: 加劳德特大学
开课时间: 2011-08-24
课程语种: 英语
中文简介:
我们探索了将语音转录纳入基于子单元的手语识别统计模型的新方向。首先,我们采用一种新的符号处理方法,根据HamNoSys符号将符号语言注释转换为根据姿势 - 滞留 - 转换 - 稳态移位语音模型的结构化标签序列。接下来,我们利用这些标签及其与视觉特征的对应来构建基于语音的统计子单元模型。我们还通过统计子单元构造和解码将这些序列与视觉数据对齐,以提取他们缺乏的时间边界信息。由此产生的语音子单元为手语分析,语音建模和自动识别提供了新的视角。我们通过扩展的希腊手语Lemmas语料库中的手语识别实验来评估这种方法,这不仅可以提高与纯数据驱动方法相比的性能,还可以在有意义的语音子单元模型中进行评估,这些模型可以在跨学科中进一步利用手语分析。 ** //免责声明://解释中可能存在错误或遗漏,因为口译员不是感兴趣的领域的专家,并且在没有全面准备的情况下进行同声翻译。**
课程简介: We explore novel directions for incorporating phonetic transcriptions into sub-unit based statistical models for sign language recognition. First, we employ a new symbolic processing approach for converting sign language annotations, based on HamNoSys symbols, into structured sequences of labels according to the Posture-Detention-Transition- Steady Shift phonetic model. Next, we exploit these labels, and their correspondence with visual features to construct phonetics-based statistical sub-unit models. We also align these sequences, via the statistical sub-unit construction and decoding, to the visual data to extract time boundary information that they would lack otherwise. The resulting phonetic sub-units offer new perspectives for sign language analysis, phonetic modeling, and automatic recognition. We evaluate this approach via sign language recognition experiments on an extended Lemmas Corpus of Greek Sign Language, which results not only in improved performance compared to pure data-driven approaches, but also in meaningful phonetic sub-unit models that can be further exploited in interdisciplinary sign language analysis. **//Disclaimer:// There may be mistakes or omissions in the interpretation as the interpreters are not experts in the field of interest and performed a simultaneous translation without comprehensive preparation.**
关 键 词: 手语识别; 语音单元; 手语识别实验
课程来源: 视频讲座网
最后编审: 2020-06-29:wuyq
阅读次数: 52