AppTek automatic dubbing technology featuring ASR, timed-MT, and adaptive TTS with voice print, prosody, volume, and emotion for natural-sounding speech.
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Natural Language Understanding (NLU) is the ‘youngest’ language technology underpinning many of today’s most exciting language-driven applications. In this Spotlight Series article, we interviewed AppTek’s Lead Science Architect for NLU, Dr. Christian Dugast, to better understand how one gets to work with NLU before this became a subject taught at universities, the issues NLU scientists work on a daily basis, as well as discuss its current status and future direction.
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AppTek's Mattia Antonino Di Gangi earned the European Association for Machine Translation's (EAMT) Best Thesis Award for his thesis "Neural Speech Translation: From Neural Machine Translation to Direct Speech Translation" (University of Trento, Italy)
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AppTek's MT technology was recently evaluated against other leading MT providers as part of Intento's 2021 State of Machine Translation report.
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Today, common approaches to automatic speech-to-speech translation haves traditionally been performed approached through cascading ASR, NMT, and TTS capabilities. AppTek scientists are seeking to streamline this process with direct textless speech-to-speech translation models.
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AppTek.ai 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), large language models (LLMs) and text-to-speech (TTS) technologies. The AppTek platform delivers industry-leading solutions 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, channels, domains and demographics.
