How to develop audio recognition software?


Technology advancements have been on a roll over the past decade. With the world moving at such a fast rate, it is no wonder you are leveraging the amazing usability of audio recognition in software. The world runs on sound, it being the most important thing that connects us with other people; the base of communication. The variety of sounds that you get to hear every day is amazing, the sound of the bustling city, the lively sounds of the forest, and the calming sounds of the ocean, sound is present everywhere. 

Audio recognition software has amazing applications which will be explored in this article. Developing the software thus depends on their application levels. People have become so familiar with virtual assistants like Alexa, Google Assistant, Siri, and Cortana that it has become permanently ingrained into their lives. With AI and then with conversational AI, especially in the field of e-commerce, businesses started using conversational commerce initiatives to communicate with their customers quite effectively. The application of audio recognition software is everywhere now! 

Applications of audio recognition software

You can implement voice recognition in so many different ways, not just to play songs on Spotify. People are getting used to the idea of using their voice to search for something, instead of ‘typing keywords and searching’. Hence, the most common application is Voice Search. Audio recognition software can also be used to:

  • Give commands to smart home devices to turn on the lights, boil water, wash clothes, adjust the thermostat, and so on. 
  • In customer services and customer interactions at call centers, it is cheaper and also it is available 24/7. 
  • Unlocking a person’s phone using not just fingerprints and facial recognition, but their voice and words too through speech biometrics.
  • In-car speech recognition software in the automotive industry where drivers can continue to drive their vehicle while making phone calls, selecting their favorite radio stations, and so on. 
  • Learning for visually impaired children and for other adults who cannot read, thereby creating an equitable learning platform
  • Capturing patient diagnosis notes and saving time for physicians when they want some quick note-taking on patient symptoms, and seeing more patients in a day
  • Speech recognition technology can understand the emotions of a person while talking with them and can help detect feelings of desperation, depression, anger, irritation, and so on. 

These are just a few of the avenues in which you can use audio recognition software, proving that audio recognition or voice recognition software will take your business to the next level of success. 

Things to consider before going ahead with audio recognition software

Before developing an audio recognition software, there are some key considerations that you have to go through. Here are some of them:

Identify the right use case for your business

Developing audio recognition software does have its complexities, so go with it only when you are assured that there is a viable use case for the technology. The best use cases have been discussed above, and so it would be easier for you to conclude how to leverage the benefits of such software. 

The features and functionalities you are planning to offer

After identifying the right use case for your business, and understanding the requirements, it would be easier for you to determine the features and functionalities of the voice software. This is how you determine the scope of the project, and what tangible value you can offer them. 

Planning for the project development life-cycle

Since it is all about AI, you have to gather a huge repository of datasets to develop a large vocabulary speech and audio recognition software. Of course, this depends a lot on the end user’s requirements. You will be making use of specific AI capabilities like Natural Language Processing (NLP), speech recognition, Deep Learning, and others to do this. You can also use features like Acoustic modeling for speech recognition and for recognizing phonemes. It is also important that you develop features like HMM or Hidden Markov Model decomposition to help understand and decipher the speech and eliminate background noise. 

Understanding the scope of the application

Before deciding on audio software, there are a few things the developers will want to know. Some of the questions they might ask you are:

  • Purpose of the applications
  • Who are the target users
  • What are the environmental conditions and ambience it will be used for
  • Understanding the features of the domain area
  • What are the plans for scalability in the future

The developer will consider a few basic audio properties before commencing to develop the software, like for example, 

  • Type of audio file format
  • Which channel to go for – stereo or mono
  • What bitrate like for example, 32 kbit/s, 128 kbit/s, and so on
  • Duration of audio clips
  • What is the sample rate value like 8kHz, 16 kHz, etc

These are the specifics of audio processing that will help the developers understand the data they need, the processing time, the segregation of the data that’s required from the collection, and so on. This field is constantly evolving, along with the advancements made in signal processing techniques and machine learning. Engaging talented developers will help with the continuous improvement and adaptation of the software because it is important to collect more data, refine the algorithms, and utilize the feedback from the users to improve their experience.

The advancements in AI will also help in perfecting the audio software applications because it is so important to extract meaningful information from the captured audio. But not just AI would be able to do it, you need to apply NLP or Natural Language Processing to make meaningful notions, understand the exact words, and make grammatical constructions from the audio.


Speech recognition technology is taking off. With more and more people resorting to their mobile phones to access, and practically search for everything in their daily life, even Gen X people are quite handy with their mobile phones. The small keyboards on mobile phones can be a bit irritating for them, and using the voice capabilities would make so easier for them to get into the groove.

Software developers embrace a multidisciplinary approach and combine machine learning, software engineering, and signal processing to create robust audio recognition software. They follow a systematic approach and employ continuous improvement and adaptation to perfect and polish the software so it works like magic. The software developers have to train and optimize the software so it can be deployed in multiple applications. They will also train the application to separate the user’s voice from other noises in the background. They will be using voice detection methods and the software will immediately capture frames that will segregate only the speaker’s voice and block out other sounds. 

Interesting Links:

A Detailed Guide to Creating a Voice Recognition Application

Where should I start if I want to create my own voice recognition system?

Pictures: Canva

The author: Sascha Thattil works at which is a part of the YUHIRO Group. YUHIRO is a German-Indian enterprise which provides programmers to IT companies, agencies and IT departments.

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