Communication has been an important aspect of human life, civilization, and globalization
for thousands of years. Biometric analysis, education, security, healthcare, and smart cities …

With the emergence of deep learning, the performance of automatic speech recognition
(ASR) systems has remarkably improved. Especially for resource-rich languages such as …

Abstract Machine lip reading recognizes text content through the speaker's lip motion
information. Lip reading has significant research and application value. With the continuous …

The primary aim of this study was to contribute to the development of multilingual automatic
speech recognition for lower-resourced Turkic languages. Ten languages—Azerbaijani …

We present the first industrial-scale open-source Kazakh speech corpus for automatic
speech recognition research and development. Our corpus subsumes two previously …

In recent years, the progress made in neural models trained on extensive multilingual text or
speech data has shown great potential for improving the status of underresourced …

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 …

Ensuring the best quality and performance of modern speech technologies, today, is
possible based on the widespread use of machine learning methods. The idea of this project …

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 …

To obtain a reliable and accurate automatic speech recognition (ASR) machine learning
model, it is necessary to have sufficient audio data transcribed, for training. Many languages …