Georg Huettenegger’s Post

Interlingual Syntactic Parsing: An Optimized Head-Driven Parsing for English to Indian Language Machine Translation

A speech translation system on Claudio Fantinuoli's website. "A speech translation system is a computer program or machine learning model that is designed to convert spoken language from one language to another. These systems use natural language processing techniques, such as machine translation and speech recognition, to analyze and translate speech in real-time. The goal of speech translation systems is to enable people who speak different languages to communicate with each other without the need for an interpreter or to learn a new language. Speech translation systems have numerous potential use cases. One important use case is in the field of international business, where companies need to communicate with customers and partners who speak different languages. Speech translation systems can also be used in travel and tourism, allowing tourists to communicate with locals and navigate foreign environments more easily. Additionally, speech translation systems have the potential to aid in emergency situations, such as natural disasters, where people from different language backgrounds may need to communicate with first responders. Despite the many potential use cases of speech translation systems, they also have some limitations. One major limitation is accuracy. While speech translation systems have improved significantly in recent years, they still struggle with certain aspects of language, such as idiomatic expressions and cultural references. Additionally, speech translation systems may not work well in noisy environments or with strong accents, making them less reliable in certain situations." A link to the website: https://lnkd.in/g9GmJ8iu? #machineinterpreting #machinetranslation #speechtranslation

MTPE – What they promise: - A faster translation - A cheaper translation - A high-quality translation And all this would be true if the reviewer simply had to scan the text and patch up a few obvious mistranslations or misunderstandings. This is how many people see the process. But it's not the reality. The reality is that machine-translated texts stick too closely to the source syntax. This means that they sound strange and unnatural. When faced with these kinds of texts, reviewers have a choice. They can either ignore the dodgy syntax and stick to what they are paid to do, ignoring all problems beyond the most glaring translation mistakes. Or they can take their time to fix up the text and produce a good translation, sometimes rewriting entire sections from scratch, essentially doing a proper job at a fraction of the cost. So the client may get a faster and a cheaper translation, but they won't get a quality one. And if they do, it's because the work has been slower and more expensive not for them, but for the linguist. #mtpe #translation #machinetranslationpostediting #localization #language #artificialintelligence #ai #chatgpt #humancreativity #humandesign

MTPE – What they promise: - A faster translation - A cheaper translation - A high-quality translation And all this would be true if the reviewer simply had to scan the text and patch up a few obvious mistranslations or misunderstandings. This is how many people see the process. But it's not the reality. The reality is that machine-translated texts stick too closely to the source syntax. This means that they sound strange and unnatural. When faced with these kinds of texts, reviewers have a choice. They can either ignore the dodgy syntax and stick to what they are paid to do, ignoring all problems beyond the most glaring translation mistakes. Or they can take their time to fix up the text and produce a good translation, sometimes rewriting entire sections from scratch, essentially doing a proper job at a fraction of the cost. So the client may get a faster and a cheaper translation, but they won't get a quality one. And if they do, it's because the work has been slower and more expensive not for them, but for the linguist. #mtpe #translation #machinetranslationpostediting #localization #language #artificialintelligence #ai #chatgpt #humancreativity #humandesign

Struggling to find skilled agents who speak specific languages? Real-time speech translation could be a solution. Our own Jakob Westgren had an interesting conversation with Erik Bouwer from the online Dutch magazine Ziptone explaining how real-time speech translation is an important and strategic part of our IT portfolio. "Transcom’s challenge is to find the right talent at the right time and at the right price. Real-time translation removes the limitations of language regions. It makes our talent pool much larger: you can work with ‘high cost languages’ in ‘low cost countries’.” Learn more: https://lnkd.in/g3i2h9rV #customerservice #ai #translation #problemsolved

BHASHINI, India’s AI-led language translation and database platform, will soon start charging enterprises and institutions based on features and service requirements, CEO Amitabh Nag told FE. #Technology #AI #Database #DigitalIndia

Let us talk again about the latest language news. Unsupervised speech-to-speech translation from monolingual data https://lnkd.in/dzYDCf6n Speech-to-speech translation is a type of machine translation that converts spoken words from one language to another. The technology has the potential to break down language barriers and facilitate communication between people from different cultures and backgrounds. Translatotron 3, a novel unsupervised speech-to-speech translation architecture, shows that it is possible to learn speech-to-speech translation from monolingual data alone. This method opens the door not only to translation between more language pairs but also towards translation of non-textual attributes of speech such as pauses, speaking rates, and speaker identity. The method does not include any direct supervision to the target languages, and it is therefore the right method for the preservation of the paralinguistic characteristics of the source speech in the translation. Back-translation is used to enable speech-to-speech translation. The quality of translation is measured using BLEU on automatic speech recognition transcriptions of the translated speech compared to the corresponding reference translation text. Speech quality is measured using the MOS score. Translatotron 3 outperforms the baseline by large margins in every aspect measured: translation quality, speaker similarity, and speech quality. It particularly excels on the conversational corpus and achieves speech naturalness similar to that of the ground truth audio samples. #janusworldwide #translation #localization #languageservices #languagesolutions #languagesupport #linguisticsupport #languagenews #languages #news #insights #machinetranslation #MT #technology

Govt. backed AI Translation platform 'Bhashini' to offer its real-time language translation service on a paid basis. Bhashini, India’s AI-led language translation and database platform, will soon start charging enterprises and institutions based on features and service requirements, CEO Amitabh Nag told FE. 》Bhashin has been developed by the Digital India Bhashini division under the Digital India Corporation 》The App has enabled features like text-to-text translation in 22 languages, automated speech recognition, text-to-speech synthesis, optical character recognition, video translation, document translation, language detection, voice-based payments, among others. 》Bhashini’s real-time translation works in 12 languages and it has improved the live translation lag from 6 seconds to 1-2 seconds now. 》Currently, 40 million inferences per month are happening on the platform. Bhashini has an app which can be used by people. 》It also provides API (application programming interface) integration to startups which want to use Bhashini’s language features on their platforms such as chatbots, etc. digitalindia.com Mangal D Karnad - Co-founder, FounderLabs Amitabh Nag Daya Prakash [TalentOnLease] #Bhashini #AIplatform #DigitalIndia #artificialintellegence #Chatbots #Texttospeech Read our Blogs at (www.founderlabs.com)

💻 ⌨ Machine translation has made impressive strides, yet translating Central and Eastern European languages remains challenging due to their morphological richness, syntax variability, and cultural nuances. 💡 This article explores these complexities, highlighting the scarcity of training data and the need for domain-specific texts. Despite advancements in neural machine translation, the gap in achieving high-quality translations persists. 👍 The future of machine translation for CEE languages lies in the combined efforts of advanced AI models and human expertise to ensure accuracy and cultural relevance. 👉 Read more about the unique hurdles and promising developments in this area in our blog post: https://lnkd.in/ecf3_Efr #CEE #language #linguistic #localization #content

🌍 Is there such a thing as an "untranslatable" word? Languages hold the beauty of culture, identity, and emotion. Some words, like gotong royong or saudade, are considered “untranslatable” because they capture unique cultural nuances. But is that really true? In our latest blog, we dive into the myth of untranslatable words, unpack their deeper meanings, and show how modern AI-powered tools can bridge even the most complex language gaps. From redefining terms like hygge to enabling real-time communication in over 120 languages, technology like VideoTranslatorAI is making seamless global connections a reality. 🌟 Curious to know how? Click the link and explore how no word—or idea—is ever truly lost in translation. Let’s celebrate the power of language and technology! 🚀 👉 https://bit.ly/41v2wVk #Language #Translation #AI #GlobalCommunication #CulturalNuances #Innovation #TechnologyForGood