Machine Translation (MT) or automated translation is a process when a computer software translates text from one language to another without human involvement. There are three types of machine translation methods: rule-based, statistical and neural networks. Current machine translation software often allows for customization by domain or profession, improving output by limiting the scope of allowable substitutions.
Machine Translation APIs uses cases
You can use Machine Translation in numerous fields, here are some examples of common use cases:
documentation and instructions: translate PowerPoint presentations, intranet bulletins, and other similar documents
email and communication: help decrease or even eliminate the language barrier in communication. A translation of the text can be obtained quickly and in a form that enables the recipients to understand the core content of the message
Top Machine Translation APIs
MT experts at Eden AI tested, compared and used many machine translation APIs of the market. There are many actors and here are actors that perform well (in alphabetical order):
Google Cloud Translation
IBM Watson Language Translator
Microsoft Azure Translator
Performance variations of Machine Translation APIs
For all the companies who use machine translation in their softwares and for their customers, cost and performances are real concerns. The MT market is dense and all those providers have their benefits and weaknesses.
Performance variations according to the languages
Machine Translation APIs perfom differently depending the language of audio. In fact, some providers are specialized in specific languages. Different specificities exist:
Region specialities: some MT APIs improve their machine translation APIs to make them accurate for text in specific language. For example: some MT APIs perform well for translating english (US, UK, Canada, South Africa, Singapore, Hong Kong, Ghana, Ireland, Australia, India, etc.), other for translating spanish (Spain, Argentina, Bolivia, Chile, Cuba, Equatorial Guinea, Laos, Peru, US, etc.), other are specialized in asian languages, etc.
Rare language speciality: some machine translation vendors care about rare languages and dialects. You can find APIs that allow you to process text in Gujarati, Marathi, Burmese, Pashto, Zulu, Swahili, etc.
Performance variations according to text data quality
When testing multiple machine translation APIs, you will find that providers accuracy can be different according to text quality and format. For example, some MT APIs perform better with text coming from tweets, others perform better with text from scientific papers, others with text from customer reviews, etc. This is explained because of the quality of the text (we can imagine that tweets are lower quality texts compared to scientific papers or press articles for example).
Performance variations according fields
Some APIs are trained their engine with specific data. This means that MT APIs will perform better for text in medical field, other in automotive field, other in generic fields, etc. If you have customers coming from different fields, you must consider this detail and optimize your choice.
Using multiple machine translation APIs is the key
All the companies that have machine translation feature in their product or deal with voice technology for their customers have to use multiple machine translation APIs. This is mandatory to reach high performance, optimize cost and cover all the customers needs. There are many reasons for using multiple APIs:
Fallback provider is the ABCs. You need to set up a MT API that is requested if and only if the main machine translation API does not perform well (or is down). You can use confidence score returned or other methods to check provider accuracy.
Performance optimization. After testing phase, you will be able to build a mapping of MT vendors performance that depend on criterias that you chosed (languages, fields, etc.). Each audio that you need to process will be then send to the best API.
Cost - Performance ratio optimization. This method allows you to choose the cheapest provider that performs well for your data. Let's imagine that you choose Google Cloud API for customer "A" because they all perform well and this is the cheapest. You will then choose Microsoft Azure for customer "B", more expensive API but Google performances are not satisfying for customer "B". (this is a random example)
Combine multiple MT APIs translations. This approach is required if you look for extremely high accuracy. The combination leads to higher costs but allows your translation service to be safe and accurate because MT APIs will validate and invalidate each others for each words and sentences.
Eden AI is a must have
Eden AI has been made for multiple machine translation APIs use. Eden AI is the future of machine translation and localization usage in companies. The Eden AI MT APIs allows you to call multiple MT APIs and handle all your voice issues:
Centralized and fully monitored billing on Eden AI for all automatic translation APIs
Unified API for all providers: simple and standard to use, quick switch between providers, access to the specificic features of each provider
Standardised response format: the json output format is the same for all suppliers thanks to Eden AI's standardisation work. The response elements are also standardised thanks to Eden AI's powerful matching algorithms.
The best machine translation APIs of the market are available: specialized engines for different languages like english (US, GB, ETC.), chinese (trad, off, etc), european languages, afrikaans languages, asian languages, esp, portugal, etc.), special engines for rare languages
Data protection: Eden AI will not store or use any data. Possibility to filter to use only GDPR engines.