How does Voice AI Understand and Handle Languages and Accents?
Communication is far more complex than it seems
There are an estimated 6,500 languages spoken in the world today according to the language learning app Busuu. A single widely spoken and global language like English can be further categorised into different dialects, while other languages have different levels of formality depending on who is speaking to whom. Throughout history, the complexity of human communication has baffled even the brightest of minds and prevented us from achieving mutual understanding.
But what if we could go anywhere in the world without having to worry about language barriers? What might the world be like if we could interact with our phones, computers, cars, and other devices the way we talk to others? This is the vision that innovators and technologists hope to achieve with natural language processing (NLP) technology.
How does voice AI understand languages and accents?
At AI Rudder, we merge technology with the power of voice communications to build a strong connection between companies and their customers. Through our innovation with AI, we have engineered voice assistants that are capable of understanding a wide variety of human speech, including dialects, slang, and nuances of formal and informal languages. With years of experience in developing voice AI across global markets, we’ve helped notable companies across banking and finance, fintech and e-commerce to improve on the scale, speed and quality of their customer interactions by helping them to automate repetitive tasks.
For voice automation to work, we must first apply Automatic Speech Recognition (ASR) — converting spoken words into machine-readable text. During the process, machines analyse the text by breaking down sentences and speech and applying lexical parsing to develop their “understanding” of the conversation.
In the event ASR fails to understand the spoken language or accent, our Voice AI goes on to disambiguate the language’s syntax or semantics by examining the context of certain keywords.
All of this is important—the more data we process, the more accurately voice A will be able to respond instead of relying on assumptions and weak correlations. It isn’t easy! Sometimes, to solve uncommon words and phrases (such as those used in the financial industry), we have to manually train our voice AI. Though this can be difficult and costly, it is necessary so that the robot can recognise the meaning and word the next time it hears it.
How do robots communicate with humans?
Humans are capable of bi-directional and omni-directional communication. Robots, however, have to be “taught” or to be more precise, programmed, to communicate back — this is called natural language generation. For this to work, our voice robots will combine ASR, natural-language understanding (NLU), and text-to-speech (TTS) functions in the following order:
- Converts human language into text via ASR
- Uses NLU/natural-language-processing (NLP) to identify the intention and arrive at an outcome
- Uses TTS to generate the response
Voice AI is rising to the linguistic challenge
Today, artificial intelligence or AI, has advanced enough to be aware of conversational context and to understand humans’ intent and sentiment. This technological advancement has enabled voice AI assistants to play a pivotal role in consumers’ everyday lives. They are able to accurately interpret customer needs, respond to questions, and nurture callers towards desired outcomes while still remaining compliant with preset guidelines.
Especially in Asia, where the languages spoken is incredibly diverse, voice AI enables B2C communications to be much more accessible and personalised. In fact, our voice assistants understand and speak ASEAN languages, such as Bahasa Indonesia, Mandarin, Thai, Hindi, Tamil, Filipino, Vietnamese, and English with regional accents. They can also automatically switch between multiple languages for better customer engagement, so your customers can always feel right at home while conveying their needs.