论文标题
应用语音节气衍生的功能，嘘声和费舍尔矢量来检测外科手术面具中的老年人情绪和言语
Applying Speech Tempo-Derived Features, BoAW and Fisher Vectors to Detect Elderly Emotion and Speech in Surgical Masks
论文作者
论文摘要
2020年言语计算副语言学挑战（比较）由三个子挑战组成，其中任务是确定老年人扬声器的唤醒和价水平，确定是否戴着外科手术面具的实际扬声器以及估计说话者的实际呼吸。在我们对挑战的贡献中，我们专注于老年人情绪和面具子挑战。除了利用标准或接近标准的功能，例如比较功能，原告词和费舍尔矢量，我们还利用情感与语音速度（即语音率）有关。为了利用这一点，我们使用ASR系统执行电话级识别，并从输出中提取功能，例如发音节奏，语音节奏和测量停顿量的各种属性。我们还假设戴上手术面具会使扬声器感到不安，导致言语较慢和更犹豫。因此，我们在面具子挑战中也尝试了相同的特征。尽管这一理论并没有通过面具亚挑战的实验结果证明是合理的，但在老年人情绪亚挑战中，我们在开发集和交叉验证中都具有这种特征类型的唤醒和价值，从而显着提高了唤醒和价值。
The 2020 INTERSPEECH Computational Paralinguistics Challenge (ComParE) consists of three Sub-Challenges, where the tasks are to identify the level of arousal and valence of elderly speakers, determine whether the actual speaker wearing a surgical mask, and estimate the actual breathing of the speaker. In our contribution to the Challenge, we focus on the Elderly Emotion and the Mask sub-challenges. Besides utilizing standard or close-to-standard features such as ComParE functionals, Bag-of-Audio-Words and Fisher vectors, we exploit that emotion is related to the velocity of speech (i.e. speech rate). To utilize this, we perform phone-level recognition using an ASR system, and extract features from the output such as articulation tempo, speech tempo, and various attributes measuring the amount of pauses. We also hypothesize that wearing a surgical mask makes the speaker feel uneasy, leading to a slower speech rate and more hesitations; hence, we experiment with the same features in the Mask sub-challenge as well. Although this theory was not justified by the experimental results on the Mask Sub-Challenge, in the Elderly Emotion Sub-Challenge we got significantly improved arousal and valence values with this feature type both on the development set and in cross-validation.
