Search Results for author: Seung Hee Yang

Found 11 papers, 2 papers with code

The effect of speech pathology on automatic speaker verification -- a large-scale study

no code implementations13 Apr 2022 Soroosh Tayebi Arasteh, Tobias Weise, Maria Schuster, Elmar Noeth, Andreas Maier, Seung Hee Yang

Therefore, we investigate in this study whether or not pathological speech is more vulnerable to such re-identification than healthy speech.

Text-Independent Speaker Verification

Disentangled Latent Speech Representation for Automatic Pathological Intelligibility Assessment

1 code implementation8 Apr 2022 Tobias Weise, Philipp Klumpp, Kubilay Can Demir, Andreas Maier, Elmar Noeth, Bjoern Heismann, Maria Schuster, Seung Hee Yang

Our results are among the first to show that disentangled speech representations can be used for automatic pathological speech intelligibility assessment, resulting in a reference speaker pair invariant method, applicable in scenarios with only few utterances available.

SliTraNet: Automatic Detection of Slide Transitions in Lecture Videos using Convolutional Neural Networks

1 code implementation7 Feb 2022 Aline Sindel, Abner Hernandez, Seung Hee Yang, Vincent Christlein, Andreas Maier

With the increasing number of online learning material in the web, search for specific content in lecture videos can be time consuming.

Does Proprietary Software Still Offer Protection of Intellectual Property in the Age of Machine Learning? -- A Case Study using Dual Energy CT Data

no code implementations6 Dec 2021 Andreas Maier, Seung Hee Yang, Farhad Maleki, Nikesh Muthukrishnan, Reza Forghani

In the domain of medical image processing, medical device manufacturers protect their intellectual property in many cases by shipping only compiled software, i. e. binary code which can be executed but is difficult to be understood by a potential attacker.

A Scalable Chatbot Platform Leveraging Online Community Posts: A Proof-of-Concept Study

no code implementations10 Jan 2020 Sihyeon Jo, Sangwon Im, SangWook Han, Seung Hee Yang, Hee-Eun Kim, Seong-Woo Kim

The development of natural language processing algorithms and the explosive growth of conversational data are encouraging researches on the human-computer conversation.


Self-imitating Feedback Generation Using GAN for Computer-Assisted Pronunciation Training

no code implementations20 Apr 2019 Seung Hee Yang, Minhwa Chung

Trained on 97, 200 spectrogram images of short utterances produced by native and non-native speakers of Korean, the generator is able to successfully transform the non-native spectrogram input to a spectrogram with properties of self-imitating feedback.

Cannot find the paper you are looking for? You can Submit a new open access paper.