Customer service operations span from small local teams to vast international networks with thousands of representatives. The primary challenge for customer support teams lies in breaking the language barrier and avoiding communication gaps. Fortunately, AI has transformed the customer service industry for the better. From accents to dialects, AI-powered text translation features decode conversations, ensuring multilingual customer support, seamless communication, and elevated brand experiences.
AI translation, also known as machine translation, uses AI algorithms to translate text from one language into another automatically. The translation function uses machine learning (ML) algorithms to analyze large amounts of text data in multiple languages and learn the relationships between words and phrases. The algorithms then use this information to translate new text in real time. The feature allows users to read translated subtitles and captions and access text transcripts in the same language from one place.
Modern artificial intelligence can understand people's intentions, needs, and desires. AI can also translate text or audio between two languages using deep learning, machine learning, neural network systems, and large language models.
AI text translation uses a neural machine translation process that relies on neural networks and large language models. It captures the context of full sentences in messages to provide accurate, fluent translations and improve communication between speakers of different languages.
AI-powered translation is a complex process. AI translators were modeled after the human brain, utilizing a neural network that processes extensive data and establishes meaningful connections within the information extracted.
Here’s a breakdown of the process:
(1) Data collection and preprocessing
The system collects textual data for translation from various sources, such as conversations, websites, documents, etc. The data is then ‘cleaned’ or ‘preprocessed.’ That means the ‘raw data’ is prepared to make it suitable for the machine learning model to understand.
Preprocessing preserves a message's context and intended meaning by removing inconsistencies from the information before translation. In addition to cleaning, profiling, and integrating input data, the data collection and preprocessing stage also filters substandard or incomplete information.
(2) Training the neural network
Training neural networks involves continuous training of artificial intelligence models with data to adapt to changing language patterns and terms. The process starts with selecting the appropriate neural network or AI model, a complex web of interconnected artificial neurons that learn from data. The chosen model is used for translation purposes.
Training neural networks involves continuous training of AI models with data to adapt to changing language patterns and terms. The process starts with selecting the appropriate neural network or AI model, a complex web of interconnected artificial neurons that learn from data. The chosen model is used for translation purposes.
Next, preprocessed data is fed into the network, where each source sentence and its corresponding translated sentence form a training pair. AI models learn through a process called backpropagation, which simulates human intelligence by acquiring and using data. The system also applies specific rules to reason information; if it reasons incorrectly, it learns to self-correct. This error correction process continues until the AI model can execute the task error-free.
(3) Encoding and decoding
Modern AI translation tools are equipped to comprehend the context, meaning, and style of text-based content, producing accurate translations that preserve the natural expression and context of the source data. To execute translation requests effectively, AI models encode and decode information.
Encoding, in human terms, involves the brain collecting, processing, and storing external stimuli meaningfully in memory, a process mirrored by AI machine learning models. These models convert unsampled data, such as a source sentence, into a numerical representation (vector) that captures its meaning.
Decoding, in human memory, is the brain's process of deciphering encoded data to understand its context and meaning. Similarly, in AI models, decoding involves generating a corresponding sentence in the target language based on the encoded representation. This iterative process predicts the most likely word in the target language one at a time until the entire sentence is translated, ensuring the translated text retains the original context and meaning.
(4) Post-processing
Texts translated by machine learning algorithms aren’t always accurate and ready to use. Decoded translations may contain grammatical errors or unnatural phrasing. During post-processing, the AI model leans on additional techniques to refine the translation, such as grammar checks, fluency checks, and stylistic adjustments. Post-processing ensures the accuracy of results.
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AI-powered translation is a boon for many industries. Here are some of the industries that benefit the most from this technology:
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Importance of translation services in customer serviceAutomatic translation is an essential requirement for all enterprises. In today’s globalized world, translation services help customer service teams overcome linguistic boundaries and empower support agents to communicate meaningfully with customers who do not speak the same language as they do. It enables effective communication and the comprehensive transmission of knowledge and information between people, promoting 360-degree cooperation.
Advantages of AI-powered text translation tools for customer service professionals:
You can gain further knowledge on delighting your customers in this informative blog: 14 Helpful Tips To Deliver Great Customer Service
OwlForce's AI-powered translation functionality goes beyond literal translations to ensure effective and accurate conversational support for your valuable customers. The AI-driven text translation feature supports 18+ languages, giving your customer care team the power to fulfill customer requests from vast demographics.
Besides allowing service teams to simplify customer communication and attend to customer tickets in multiple languages, OwlForce's AI-driven text translation benefits enterprises by ensuring real-time customer interactions, consistent quality and precision in customer communication, and optimized workflows. Try OwlForce by ThinkOwl to explore the wonderful AI—and automation-driven features.