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A Continuous Prominence Score Based on Acoustic Features

机译:基于声学特征的连续突出分数

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Up to now, prominence detection has mainly been considered a binary matter, a syllable or a word being considered as prosodically prominent or not. This contribution aims at developing an automatic detection procedure of gradual prominence. Based on 4 prosodic parameters (relative duration, relative f0, f0 movement and pause duration), the system provides each syllable with a gradual score of prominence ranging from 0 (non-prominent syllable) to 4 (extra-prominent syllable). The automatic detection (ProsoProm) relies on a manually annotated corpus (18 minutes, or 3669 syllables, of speech annotated by three experts) and is cumulative (the relative weight of each parameter is taken into account in order to compute a global score for each syllable). The discussion of the results includes a qualitative analysis of misses and false detections. The agreement between automatic and (median) human annotation reaches a Kappa score of 0.8.
机译:到目前为止,突出检测主要被认为是二进制物质,一个音节或一词被视为虚拟突出的词。这一贡献旨在开发逐步突出的自动检测程序。基于4个韵律参数(相对持续时间,相对F0,F0移动和暂停持续时间),系统提供每个音节,其突出的分数从0(非突出音节)到4(超出突出音节)。自动检测(PROSOPROM)依赖于手动注释的语料库(由三位专家注释的语音18分钟,或3669个音节),并且累积(考虑每个参数的相对权重,以计算每个的全局分数音节)。结果的讨论包括对未命中和错误检测的定性分析。自动和(中位数)人类注释之间的协议达到了kappa得分为0.8。

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