McLEAN, Va., Aug. 3, 2021 /PRNewswire/ — AppTek, a leader in Artificial Intelligence (AI), Machine Learning (ML), Automatic Speech Recognition (ASR), Neural Machine Translation (NMT), Text-to-Speech (TTS) and Natural Language Processing / Understanding (NLP/U) technologies, today announced the appointment of Dr. Zoltán Tüske as Senior Research Scientist for the company’s ASR technologies. In this role, Dr. Tüske will seek to further advance the performance of large vocabulary continuous speech recognition systems critical to the next generation of speech-enabled AI technologies.
"Our mission is to advance the science behind automatic speech recognition and provide the most accurate solution in the field" stated AppTek’s Chief Speech Scientist Eugen Beck. "Zoltán is one of the great minds in this industry and we are excited to have him on the team to collaborate on new and innovative ways to advance the science even further."
Dr. Tüske brings over 15 years of experience in speech recognition technologies with a focus on neural networks, signal processing, feature extraction, acoustic modeling, multilingual modeling, and language modeling. Prior to joining AppTek, Tüske was a Research Scientist at IBM’s AI Speech Technologies research group. Dr. Tüske has an h index of 20+ with over 1300 citations in Google Scholar, holds 4 patents, and was the recipient of the ISCA Award for the best student paper at Interspeech 2014. He holds a Ph. D. in Computer Science from RWTH Aachen University’s Human Language Technology and Pattern Recognition Group, and an M. Sc. in Electrical Engineering from Budapest University of Technology and Economics.
"I am thrilled to have Zoltán on board," said AppTek CEO Mudar Yaghi. "We are very fortunate to attract yet another leading speech scientist and further bolster our commitment to delivering state-of-the-art advancements in automatic speech recognition, neural machine translation, text-to-speech, natural language understanding and conversational AI. It’s a testament to the team and culture here to attract talent of Zoltán’s caliber."
Dr. Tüske’s recent work focuses on the research of "end-to-end" speech recognition models which map a sequence of acoustic features to a sequence of words for large vocabulary continuous speech recognition tasks such as analyzing conversational telephony. While it is widely believed that such sequence-to-sequence recognition models are competitive with traditional hybrid statistical ASR models only when a large amount of training data is used, Dr. Tüske’s team has been able to demonstrate state-of-the-art performance on a small amount of training data using an attention-based encoder-decoder sequence-to-sequence model as highlighted in the scientific paper "Single headed attention based sequence-to-sequence model for state-of-the-art results on Switchboard."
"I’m eager to join AppTek and its talented team of scientists," said Dr. Tüske. "I look forward to working closely with the team to further advance the state-of-art for speech recognition performance."
For more information, visit http://www.apptek.com.
About AppTek
AppTek is a global leader in artificial intelligence (AI) and machine learning (ML) technologies for automatic speech recognition (ASR), neural machine translation (NMT), natural language processing/understanding (NLP/U) and text-to-speech (TTS) technologies. The AppTek platform delivers industry-leading, real-time streaming and batch technology solutions in the cloud or on-premises for organizations across a breadth of global markets such as media and entertainment, call centers, government, enterprise business, and more. Built by scientists and research engineers who are recognized among the best in the world, AppTek’s solutions cover a wide array of languages, dialects and channels. For more information, please visit http://www.apptek.com.
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SOURCE AppTek
