Interactive
AppTek Launches New Multi-Lingual Collaboration Mobile Apps (MESA)
Story Highlights
AppTek, which specialises in automatic speech recognition (ASR), neural machine translation (NMT), and natural language understanding (NLU), all enabled by artificial intelligence (AI) and machine learning (ML), has debuted two new speech technology applications — AppTek Speech Translate and AppTek Speech Transcribe —now available, free, via the Apple App Store.
The pair of apps feature real-time advanced speech-to-speech, speech-to-text and text-to-speech capabilities, covering a wide range of langauges, including Arabic, Brazilian Portuguese, Chinese Mandarin, Dutch, French, German, Greek, Hebrew, Italian, Japanese, Korean, Pashto, Persian Russian, Spanish and Turkish. Additionally, users of both apps can access a variety of dialects, covering a dozen Arabic, two French, three Spanish, five English, two Swiss German, and two Portuguese.
“By making both AppTek Speech Translate and AppTek Speech Transcribe available through the world’s leading digital distribution platform, we are offering the benefits of powerful real-time, next-generation ASR, NMT and text-to-speech to anyone who wants to take advantage of them,” said AppTek CEO Mudar Yaghi. “These simple-to-use and highly accurate applications enable users to speak fluently in multiple languages across a wide range of domains including travel, healthcare, conversational and more, greatly enhancing communications in a breadth of situations.”
AppTek Speech Translate is a two-way speech communication app offering conversational real-time streaming speech-to-speech translation, giving users the ability to speak directly into devices to transcribe and simultaneously translate spoken content in real-time.The app offers access to 100 pre-loaded offline phrases to help in emergency, medical, transportation and dining situation.
AppTek Speech Transcribe simplifies the transcription experience for consumers while providing accuracy, offering a reliable way to transcribe voice memos, lectures, meetings, interviews and other spoken audio content into text.
