We develop and customize Machine Translation systems that scale to millions of end users in social networking, global messaging and content management systems, increasing the valuation of any asset that globalizes using our technology.
We are on the cutting edge of machine learning, computational linguistics, artificial intelligence, and globalization of e-commerce, messaging systems and collaboration and social networking platforms in a fast growing $35 billion global market for language technology growing rapidly mobile and in the cloud.
Machine translation provides significant benefits to a wide range of applications. To get the best performance out of a commercial MT system, though, you need to customize the system to your environment's specific requirements.
"Raw machine translation" without expensive micro glossaries and linguistic customization, and translation memory, is much less accurate than customized quality for scalable real-time language translation but it is not easy to demonstrate "before and after tests" without an in-depth customization process that takes weeks. We have credible references to prove it exists and we have the capacity. We also add rapid human post-editing online for publication accuracy.
Our issued patent offers us an exclusive capability for the actual customization and integration of customized linguistic data, including micro glossaries and terminology that matches the customer needs. Adding words to a spell-checker is a rough analogy. However, there are sophisticated metrics for measuring and benchmarking machine translation quality to levels that are higher than Google Translate and other online real-time translation servers.
Common issues that we help resolve include:
assessing readiness for deploying Machine Translation and rapid human post-editing of machine translated text for short-shelf life information like real-time messaging, text to speech, and speech to text for instant messaging and dialogues, in social networks, tourism dialogues, e-commerce fulfillment dialogue, customer service dialogue where informal non-accurate translation is acceptable and emergency communications where publication accuracy is not feasible due to the short-time frames for communications and lack of scalability of human simultaneous interpretation creating bottlenecks in multi-lingual communications.
identifying the advantages and disadvantages of different MT products,
lack of client-specific or domain-specific terminology,
lack of systematic evaluation and QA procedures,
troubleshooting problems with existing installations
Our methods. We work with your team to identify a client's specific requirements and build a roadmap for deploying or optimizing translation automation. We've been developing, testing, and integrating commercial MT systems for 16 years and have developed the methods and techniques that you need to identify and solve any problems that you have with your MT installation.
Customers with a translation project to select from a variety of translation method options, ranging from a completely human translation to a completely automated translation.
For human translations, translation job information may be communicated through one or more network service modules which execute within a network service application, such as a web-based networking application.
A network service module may register a user having an account with the network service application as a translator and communicate translation jobs to the user.
One or more users who express interest in performing the translation are selected to perform a translation job, each job comprising at least a portion of the translation project.
After a user provides a translation for the translation job, the translation is analyzed to generate a trust level prediction for the translation. A user translation profile may be updated after each translation to reflect the user's performance.
Testing and evaluation of machine translation can not be done casually by entering a test phrase at random into a machine translation text translation engine--it will result is non-systematic errors using out-of-sample data that is not statistically significant, and in fact, would be highly misleading.
Rigorous testing, which Transclick has done by objective third party experts, using the BLEU and NIST machine translation evaluation metrics, the world standard for evaluating machine translation output quality, is the only way to evaluate machine translation effectiveness.
Our approach to machine translation
Immediate insight into texts in foreign languages regardless of volume and format Professional post-editing: manage the quality of automated translation depending on your requirements Translation delivery time and cost reduction of 30-50% MT solutions customized for particular company or industry MT post-editing services at a competitive rate.
Adjustable delivery models: from SaaS to on-premise Integration of automated translation into corporate content management systems and workflows
Confidential translations Statistical (SMT) engines analyze the source language based on existing lexical resources, such as good quality translation memories and terminology databases, to select the most appropriate translations in the target language.
Providing high quality data is paramount to ensure desired MT output. Rule-based (RBMT) engines analyze grammar in each segment and then invoke specific rules to derive target from source for a given language pair.
These engines also analyze syntactic structure of the source sentence trying to adapt it to common target language patterns. Model-based (MBMT) engine that uses full semantic and syntactic analysis of source text prior to translation.
Delivering efficient MT solutions
Our expertise includes working with three types of machine translation systems: We go several steps further by combining controlled language, translation memory and MT systems all of which are enhanced by our own semantic, morphological and lexical analysis tools. This customization based on individual client's data ensures maximum quality of the output before it is sent to post-editing.
Specific scenario (raw or post-edited MT) is always up to the client. In any case our job is to deliver an MT solution that saves both time and money… and keeps operational overhead low.