Developing Regional Languages Based AI Speech recognition system
AI-based voice assistants are a rapidly growing technology with almost limitless potential in the world of business and personal usage. They are not only improving the efficiency of processes, but also creating altogether new levels of personalization and user experience globally. When we talk of personalization, regional languages play a great role in making any person feel at ease. In a country as large as India, there is a great diversity of languages. Apart from English, which is widely spoken throughout the country, there are 22 scheduled regional languages identified by the constitution. Thus, the importance of AI Speech Recognition tools that can process these regional languages becomes much greater in the country. We all have already experienced the feel of this diversity while making interstate calls and being greeted by recorded IVR in Punjabi, Gujarati, Marathi or Tamil depending on the location of the person we are calling.
To understand how AI-driven voice assistants process a particular language, we need to take a look at the steps involved in the process. In simple words, the process requires the AI tool to capture the spoken word and turn it into text, match it with the database and then provide output which is converted into voice and offered to the user.
The entire process of analysing the voice sample has a number of steps involved in it. Once the audio input is received as a live audio stream or signal (wav, mp3 or any other common format). The system first improves the quality of the audio input by removing ambient noises and processing the audio file to enhance the audio signal’s performance. In the next stage, the focus is on identification of the individual speaker/s or multiple voices in the audio piece. This is an extremely crucial part of the process because wrongly identifying or not being able to identify the individual speaker is unlikely to yield desired results.
The entire audio is then segmented into smaller parts and sent to the automatic speech recognition system. The system has the ability to identify the language being spoken in the audio file and accordingly, model the audio inputs. For instance, if a user is speaking in Hindi or Bengali, the audio file will be modeled accordingly. This is the broad overview of Mihup’s AI-driven speech recognition system. Further, Mihup runs deep research on accents and local dialects across regional languages. Today, the company offers tools that accurately understand English, Hindi, Bengali, Hinglish and Benglish (Bengali mixed with English), and is currently working on developing various other regional language abilities to further enhance the experience for native speakers of other languages.
Non-American users find it 30% harder than the Americans to get understood by the existing western origin voice assistants. In this light, Mihup is creating technologies which will transform the world of automation and smart AI-based voice assistants in India as well as in countries around the world.
