Nowadays, with the emergence of new technology, the way of communication has changed. For example, when we call large enterprises, natural people will never answer our calls. Instead, automatic voice recording answers and instructs you to press the button to browse the built-in menu. Many mobile application development companies have come up with ideas that go beyond just a click of a button. Customers only need to say a few words to solve their questions.

How is that possible? This is because speech recognition programs can use algorithms to work through acoustic and language modeling. Acoustic modeling represents the connection between language units of speech and audio signal, while language modeling matches sound with word sequence to distinguish words that sound similar.

The software can be used in families and enterprises, which enables users to speak with computers and convert their words into text through word processing and speech recognition. You can access function commands, such as setting alarm clock, opening files, booking in your favorite restaurant, etc. On the other hand, some mobile applications are used for precise business settings, such as medical or legal records. The unreliability of speech recognition is the reason. Sometimes, word recognition platforms cannot understand accents or speech disorders. And it’s not enough just to recognize sounds – software must also recognize new words and proper nouns.

The world is full of smartphones, smart cars and smart devices, but we don’t always think about the role voice plays in these devices. Speech recognition is very complicated! Suppose, for example, how a child learns a language. From the day the children are born, the sound surrounds them. Although very young children don’t understand these words, they absorb all the cues and sounds, and their brains form patterns and connections based on how their parents communicate.

Some information about speech recognition technology

The working principle of speech recognition technology is basically the same: users call speech recognition on mobile applications to say some words. Speech is processed by recognition software and converted into text. Then the transformed text is provided as input to the search mechanism, which returns the results. Google’s machine learning algorithm has reached 95% of the accuracy of English words.

Easier, faster: initially, the only option for passing commands was to use the keyboard. Through speech recognition, communication with devices becomes faster and more natural. Precise operation: to avoid errors, users can focus on what they are doing without looking at the phone. Improve productivity: voice based mobile applications provide simplified operations, thereby improving operational efficiency. Improved security: voice technology can be interpreted and followed quickly and safely, and requires less training. Multiple uses: voice based commands from mobile devices help with tasks. Why is it important

By integrating voice recognition skills into your mobile app, you can do more without using your phone’s keyboard. When texting someone, typing long sentences can lead to errors, and it’s always boring, but with voice function, you can enjoy the experience of hands-free communication. With the help of voice technology, mobile application developers can increase user interaction and user experience, because mobile application commands provide a unique way to solve UX problems. Whether you want to avoid distractions or you can’t manipulate the touch screen, voice assistant is the simplest solution.

Real time response behavior: real time response depends on network function, network connection and microphone of the device. When users provide voice commands, mobile applications must interact with the server to convert voice data into text. After the text is converted and sent back to the device, the operation can be performed. The process of sending and receiving application behavior is called real-time response behavior. If the defined action is a search, the device sends another request to the server to get the result. In this case, network latency can be the most challenging thing. To solve this problem, developers must ensure that the source code of the application is properly optimized. In addition, they can move voice recognition and search functions to the server. Languages and accents: each software does not support all languages, and developers need to identify areas of the target audience in order to make strategic decisions about recognized languages or accents.

Baidu: a technology from China that focuses on Internet related services and AI. This speech recognition technology is a combination of deep learning, computer vision, speech recognition and synthesis, natural language understanding, data mining and Bi. It relies on deep learning algorithm, which includes multi-layer virtual network of training neurons to recognize patterns of big data. The baidu mobile app allows users to search using voice with a voice assistant called duer. Voice queries are more popular in China because it takes more time to enter text and some people don’t know how to use pinyin. Siri: the “Hey Siri” function enables the user to call the handsfree communication mode. Siri works much better in IOS 7 than in earlier versions. Siri responds faster, understands more, and speaks more naturally.

Speech recognition technology has indeed come a long way, and with the fierce competition among mobile application development companies, the progress of speech recognition technology is our way forward.

     

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