Machines are developing so fast that multinational tech giants are competing for neck and neck to leverage concepts like artificial intelligence (AI) and machine learning (ML) in high-tech solutions across various industries. The language industry is no exception; cutting-edge technologies started to jump in and revolutionize the traditional linguistic approaches, making way for smart computational linguistics and bright future prospects.
In this blog, we try to shed some light on the most advanced translation technologies as well as some futuristic views on how high-tech discoveries would alter the language industry.
Read on and find out some interesting research-based facts about the progress and evolution of machine translation services within multiple language solutions.
The beginning of technology-driven language solutions came with the introduction of automatic speech recognition (ASR) capabilities by which machines can recognize audio files and put them in writing. The application of AI-driven natural language processing allowed the automatic creation of real-time captions. Automatic transcription is now offered by many translation vendors at high accuracy and affordable prices.
Neural Machine Translation (NMT)
Although the general concept and early attempts of machine translation service date back to the beginning of the past century, the business of machine translation has passed through many milestones and achieved several breakthroughs.
The latest machine translation techniques are referred to as neural machine translation (NMT), or translation that depends on neural machine learning or deep learning to create an accurate and precise translation. NMT usually feeds on data and translation memories and becomes able to develop themselves, analyze the context, and provide a high-quality translation.
Simultaneous speech translation
Known also as speech-to-text translation, this technology is concerned with translating acoustic speech signals into text in a foreign language. Conducting simultaneous translation combines ASR with NMT algorithms to create an instant written translated content.
Simultaneous translation can be offered through live translated captions or post-speech translated transcripts. Google’s researchers have recently studied two simultaneous translation techniques, namely streaming vs re-translation and found out that the latter, which allows real-time editing, came out with better results in terms of quality and latency.
Among all translation technologies, automatic dubbing seems to be the most challenging function. The newly born technology involves transcribing speech to text and translating that text into another language before generating speech from the translated text and offering it in real-time.
The first part of the process is actually the same as the regular speech-to-text translation, while the second part is concerned with the challenges of converting the text into a speech that matches original timbre, emotion, duration, prosody, background noise, as well as reverberation.
Synchronizing the translated speech in a video at the maximum quality and minimum latency sounds more like human interpretation services, and it marks a real challenge in front of technology experts.
The concept of machine translation is progressing at unprecedented speed and the volume of its market is projected to exceed $983.3 million by 2022. Many tech giants are now attempting to develop smart ML-powered translation services, and we are most probably witnessing the precursors of a new era of the language industry. Hereunder, we showcase some of these remarkable attempts:
The world’s leading technology service provider has recently announced the launch of its new “Transcribe” feature which allows recording spoken words in one language and have them translated in near real-time. The new feature is much more advanced than Google Translate’s current transcription feature.
Google Assistant also now has a new Interpreter Mode, which translates real-time conversations in 29 different languages, including Thai, Slovak, and Hindi. The feature has been already used by professional players in the leisure and travel & tourism industries.
E-commerce and technology giant has recently revealed plans to release a novel “speech-to-speech” solution that leverages AI and provides automatic dubbing services. The new solution will align the translated speech with the original one, taking into account speech duration, background noise, and reverberation.
Following a fluency-based criterion, Amazon’s new service involves additional synchronization capabilities such as the ability to extract background noise and re-insert it with the translated speech.
By the end of 2019, US-based Waverly Labs introduced the real-time speech translation technology across its new earpiece, dubbed “the Ambassador”. Once connected with your phone, the ambassador pair offers instant speech recognition and translation within a radius of 8 feet. Waverly Labs’ innovative product is linked to neural networks and capable of interpreting 20 languages and 42 dialects.
Across its smart devices and advanced operating systems, Chinese telecom giant Huawei is now offering an automated translation of meeting transcripts in two languages.
The rapid digital transformation in the language industry highlights the importance of dealing with a reliable translation service provider with a technical background; a vendor who is up to date with the machine translation technologies and ready to provide tech-driven and cost-effective solutions.
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