Ivan Kukanov

University of Eastern Finland | UEF · School of Computing

Embeddings play an important role in many recent end-to-end solutions for language processing problems involving more than one data modality. Although there has been some effort to understand the properties of single-modality embedding spaces, particularly that of text, their cross-modal counterparts are less understood. In this work, we study a jo...

Since the invention of cinema, the manipulated videos have existed. But generating manipulated videos that can fool the viewer has been a time-consuming endeavor. With the dramatic improvements in the deep generative modeling, generating believable looking fake videos has become a reality. In the present work, we concentrate on the so-called deepfa...

The paper is a work in progress report on the development of DigiMo, a chatbot with emotional intelligence. The chatbot development is based on a data collection and annotations of real dialogues between local Singaporeans expressing genuine emotions. The models were trained with Cakechat, an open source sequence-to-sequence deep neural network. Pe...

Bottleneck features (BNFs) generated with a deep neural network (DNN) have proven to boost spoken language recognition accuracy over basic spectral features significantly. However, BNFs are commonly extracted using language-dependent tied-context phone states as learning targets. Moreover, BNFs are less phonetically expressive than the output layer...

The I4U consortium was established to facilitate a joint entry to NIST speaker recognition evaluations (SRE). The latest edition of such joint submission was in SRE 2018, in which the I4U submission was among the best-performing systems. SRE'18 also marks the 10-year anniversary of I4U consortium into NIST SRE series of evaluation. The primary obje...

This work tackles the problem of the domestic audio tagging or environmental sound classification, where one audio recording can contain one or more acoustic events and a rec-ognizer should output all of those tags. A baseline model for this task is a convolutional recurrent neural network (CRNN) with sigmoid output nodes optimized using the binary...

This article describes the systems jointly submitted by Institute for Infocomm (I$^2$R), the Laboratoire d'Informatique de l'Universit\'e du Maine (LIUM), Nanyang Technology University (NTU) and the University of Eastern Finland (UEF) for 2015 NIST Language Recognition Evaluation (LRE). The submitted system is a fusion of nine sub-systems based on...

We have recently proposed a universal acoustic characterisa-tion to foreign accent recognition, in which any spoken foreign accent was described in terms of a common set of fundamental speech attributes. Although experimental evidence demonstrated the feasibility of our approach, we belive that speech attributes , namely manner and place of articul...