Picognizer: A JavaScript Library for Detecting and Recognizing Synthesized Sounds
Picognizer: A JavaScript Library for Detecting and Recognizing Synthesized Sounds
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DOI：
10.1007/978-3-319-76270-8_24
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发表时间：
2017-12
期刊：
影响因子：
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通讯作者：
K. Kurihara;A. Itaya;Aiko Uemura;Tetsuro Kitahara;K. Nagao
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文献类型：
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作者：
K. Kurihara;A. Itaya;Aiko Uemura;Tetsuro Kitahara;K. Nagao
在本文中，我们描述并评估了 Picognizer，这是一个 JavaScript 库，它使用模板匹配方法检测和识别用户指定的合成声音。在日常生活中，人们被各种合成声音所包围，因此建立一种识别这些声音作为调用信息系统的触发器的方法是很有价值的。然而，让最终用户程序员通过监督学习为每个使用场景创建定制的识别器并不容易。因此，通过关注每次重放的听觉偏差较小的合成声音的特征，我们实现了一个 JavaScript 库，该库使用传统的模式匹配算法来检测和识别声音。我们定量评估了其性能，并通过提出各种使用场景（例如数字游戏的自动播放系统以及包括游戏化在内的数字游戏的增强）来展示其有效性。
In this paper, we describe and evaluate Picognizer, a JavaScript library that detects and recognizes user-specified synthesized sounds using a template-matching approach. In their daily lives, people are surrounded by various synthesized sounds, so it is valuable to establish a way to recognize such sounds as triggers for invoking information systems. However, it is not easy to enable end-user programmers to create custom-built recognizers for each usage scenario through supervised learning. Thus, by focusing on a feature of synthesized sounds whose auditory deviation is small for each replay, we implemented a JavaScript library that detects and recognizes sounds using traditional pattern-matching algorithms. We evaluated its performance quantitatively and show its effectiveness by proposing various usage scenarios such as an autoplay system of digital games, and the augmentation of digital games including a gamification.