What Is Multilingual ASR (MLASR )?
Automatic speech recognition (ASR) is a technology that converts spoken language into text. Think of when you ask a virtual assistant on your phone a question and it transcribes your words in real-time, that’s ASR in action.
While this technology is already widely used in personal and professional contexts, the ability to communicate across languages is becoming more and more important for businesses. Whether to engage global customers or offer support to different regions, multilingual communication is essential.
Multilingual ASR (MLASR) takes things a step further by enabling ASR in multiple languages. Not only does this technology help detect different languages, but it can switch between them seamlessly, fitting right into diverse settings.
In this post, we’ll examine MLASR and look at how it works, the components it involves, its benefits and limitations, and how it’s applied in the real world including aiOla speech AI’s multilingual capabilities.
How Does Multilingual ASR Work?
Multilingual ASR works by processing spoken language through a series of steps. Traditional automation speech recognition systems work through a combination of artificial intelligence and machine learning, through either deep learning models or a hybrid model.
First, ASR systems use algorithms to detect language and its nuances and then match sounds to works within that language to generate text in real-time. This process is done through a series of models, such as lexicon, acoustic, language, and decoding. Each of these complex machine learning models is trained on vast datasets for each language.
Building a multilingual system isn’t simple as the process above needs to be replicated for each language. This presents the challenge of guaranteeing accuracy across different accents, dialects, and regional slang. For developers to overcome this, they need to balance the model size and speed to support multiple languages which requires a lot of data and processing power.
That said, MLASR systems are evolving quickly to respond to the growing need for diverse language models, and are helping bridge language gaps in the workplace and making it easier for people all over the world to communicate.
The Components of Multilingual ASR
For MLASR to work smoothly, there are multiple components that need to work together to decode speech across multiple languages. Here’s a look at the key building blocks behind this speech recognition technology.
Acoustic Models
Acoustic models recognize sounds in different languages by analyzing unique audio patterns. These models are trained to capture variances in pronunciation, tone, and accents, helping the ASR system understand speech more accurately.
Language Models
These models are meant to predict the flow of words in a phrase in order to make understanding context and meaning smoother for the ASR system. Language models help these systems guess what words come next based on context. In a multilingual system, this can be helpful for languages with different grammar rules or word orders.
Pronunciation Dictionaries
These dictionaries act as suppositories that help systems understand and map out how words sound in each language. They’re meant to guide ASR systems by offering examples of how words and commonly pronounced to improve accuracy.
Multilingual Speech Corpus
This refers to a huge database of recorded speech in various languages, which is used to train automatic speech recognition models using real-world examples. Multilingual speech corpus databases make it easier for ASR systems to handle varied voices and accents.
The Benefits and Challenges of Multilingual ASR
There are many benefits that come along with systems that employ multilingual ASR, however, there are also challenges to implementing it correctly. Here’s a closer look at the benefits and challenges that come with MLASR.
Benefits
- Improved accessibility: Communication can open up for people with accessibility limitations, such as the hearing impaired, or people with language barriers
- Enhanced global reach: Companies can connect with new audiences in multiple languages, expanding their market presence worldwide
- Cost-effectiveness: With one ASR system to handle multiple languages, the need for separate tools is reduced, allowing teams to cut costs related to multilingual support
- Cultural inclusivity: By supporting a wide range of languages, MLASR opens the door for a more inclusive environment where people feel represented and understood
Challenges
- Handling diverse accents and dialects: Variations in how words are pronounced can make it tricky for ASR systems to capture every accent with the same level of accuracy
- Code-switching and language mixing: Fluctuating or code-switching between languages mid-sentence can affect accuracy, making it harder for ASR systems to consistently track speech
- Resources scarcity for less common languages: Limited training data for rarer languages can make it more challenging to offer reliable MLASR for everyone
Applications of Multilingual ASR
Multilingual employees are increasingly in demand, but accommodating them can be a challenge. In fact, according to a survey, 56% of businesses agree that their demand for multilingual speakers will increase in the next few years. Multilingual employees are essential when for business development purposes as they can help companies grow into new markets.
MLASR systems can help companies rise to this challenge, making it easier for workforces and customers to connect across different languages. It has multiple applications across different types of workflows and fields, making it a versatile tool that can be helpful in many scenarios. Here’s how it’s being applied today:
- Global business communications: MLASR is facilitating cross-border communication for many businesses, helping with smoother collaboration and meetings that bypass language barriers
- Customer service and support: The customer experience can be improved by supporting multiple languages, allowing customers to feel understood and taken care of no matter where they’re from
- Content localization: Multilingual ASR systems can streamline content translation, making it simpler for companies to reach audiences with culturally relevant messages in their preferred language
- Education and language learning: MLASR helps educational platforms support diverse languages, making language practice more accessible and making it easier for students to learn new languages
- Automotive and transportation: From voice-activated controls in vehicles to multilingual navigation systems, MLASR is helping transportation teams create safer and more intuitive experiences for all employees
aiOla’s Multilingual ASR Solution
aiOla offers speech AI technology that assists frontline workers in multiple industries with data collection and workflow automation through spoken language. With aiOla, workers can cut down essential workflows to just a few seconds, while the technology gathers essential data to inform high-level decisions entirely through speech.
As a multilingual technology, aiOla’s AI-powered speech recognition technology has the unique benefit of fitting seamlessly into any global environment while still functioning at peak accuracy. aiOla can:
- Understand over 120 different languages
- Comprehend different accents and dialects
- Grasp industry jargon in any language
- Operate in any acoustic environment
aiOla is particularly adept at handling complex workflows in industries like fleet management, transportation and logistics, and manufacturing. For example, delivery workers who are dispersed around a local area or even around the globe can all use aiOla in their native languages to complete workflows like vehicle checks, inspections, and communication. This can help companies keep all their data streamlined and organized, no matter how spread out their workforce is.
Multilanguage Systems: A Necessity in Any Industry
Multilingual systems give companies the ability to integrate their global efforts so that their work and workforce are more unified, giving businesses the opportunity to bridge gaps between locations, teams, and employees. With multilingual speech solutions like aiOla, companies can rest assured that workflows are being completed at peak efficiency while still keeping environments inclusive and accessible for all.
Book a demo with one of aiOla’s experts to see how our multilingual speech AI solution can help you improve your business.
