activity
20192021
most citedA Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and English

2 citations · 2 across the 2 of their papers we have counts for

collaborators

7 papers

eess.AS20212 cited

A Study of Multilingual End-to-End Speech Recognition for Kazakh, Russian, and English

Saida Mussakhojayeva, Yerbolat Khassanov, Huseyin Atakan Varol

We study training a single end-to-end (E2E) automatic speech recognition (ASR) model for three languages used in Kazakhstan: Kazakh, Russian, and English. We first describe the dev…

eess.AS2021

USC: An Open-Source Uzbek Speech Corpus and Initial Speech Recognition Experiments

Muhammadjon Musaev, Saida Mussakhojayeva, Ilyos Khujayorov +3

We present a freely available speech corpus for the Uzbek language and report preliminary automatic speech recognition (ASR) results using both the deep neural network hidden Marko…

eess.IV2021

Input Agnostic Deep Learning for Alzheimer's Disease Classification Using Multimodal MRI Images

Aidana Massalimova, Huseyin Atakan Varol

Alzheimer's disease (AD) is a progressive brain disorder that causes memory and functional impairments. The advances in machine learning and publicly available medical datasets ini…

eess.AS2021

KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset

Saida Mussakhojayeva, Aigerim Janaliyeva, Almas Mirzakhmetov +2

This paper introduces a high-quality open-source speech synthesis dataset for Kazakh, a low-resource language spoken by over 13 million people worldwide. The dataset consists of ab…

cs.HC2020

SpeakingFaces: A Large-Scale Multimodal Dataset of Voice Commands with Visual and Thermal Video Streams

Madina Abdrakhmanova, Askat Kuzdeuov, Sheikh Jarju +3

We present SpeakingFaces as a publicly-available large-scale multimodal dataset developed to support machine learning research in contexts that utilize a combination of thermal, vi…

eess.IV2020

End-to-End Deep Diagnosis of X-ray Images

Kudaibergen Urinbayev, Yerassyl Orazbek, Yernur Nurambek +2

In this work, we present an end-to-end deep learning framework for X-ray image diagnosis. As the first step, our system determines whether a submitted image is an X-ray or not. Aft…