Key Components for a Development of a Speech-To-Text Transcription Technology

When you think of speech recognition and the ability of computers to recognize words, you probably think of modern devices such as Siri and Alexa. You wouldn’t be wrong, and the market for such software is constantly growing.

The first speech-recognition machine ever was introduced by IBM in the distant year of 1962. This machine, called “Shoebox”, wasn’t perfect, but it set a foundation for the increased accessibility of computers. In the last decade, this technology was refined even further by using artificial intelligence and machine learning in the development process.

Speech-to-text technology, or speech recognition technology, has been finding new ways of implementation in the past few years. From virtual assistants to healthcare, this technology has been improving the lives of many people.

In this article, we will explain some of the key features of this technology and what are the necessary components of speech-to-text technology.

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Speech-to-Text technology explained

Speech-to-text technology, also known as speech recognition, is a technology that converts human speech into its transcription. This technology has many uses, and its been in constant development to be more precise and effective.

However, in spite of the efforts of corporations to perfect this technology, it’s far from being 100% accurate. But it has some benefits over manually transcribing speech. This technology is cost-efficient as it saves both time and the budget that would be used to pay a human to do a transcription.

While varying in accuracy, different platforms are using various methods to give their customers a fast way to create transcriptions. The lack of accuracy implies that, in the end, the final transcript will still require human input to be presentable to the audience. An editor might require a certain budget, but it’s still more affordable than paying someone for a complete transcription.

The quality of the recording is another thing to consider. The clearness of the language in the recording will leave the biggest impact on the accuracy of the transcript. Background noise should be eliminated or minimized.

Uses for speech-to-text

If you want to convert an audio recording into a text transcript, you might want to look for a software that’s specialized for your field of work. As mentioned before, there are multiple speech recognition algorithms, and each of them excels at a particular task.


Podcasts have become a big thing in the past few years. From podcasts that cover various topics to niche-specific ones, their popularity increased. The main reason behind this is the convenience of listening to an exciting topic without having to sit down and read it.

However, there are many people that can’t enjoy the audio content because they have trouble hearing or because they can’t understand the language. By using speech-to-text technology, you will be able to create readable transcriptions and increase the accessibility of the content.

Translations & captions

Transcriptions also increase the chances of non-English speakers discovering and enjoying your content. Whether that’s a podcast or short videos, it’s much easier to translate transcription than to translate a video directly.

Of course, it’s important that the transcription is accurate for the translation to be accurate as well. To make your content easier to follow, you can use English or the language in which you translated the content to create captions for your videos.

Captions are essential in videos that have a more professional tone of voice as it allows the viewers to understand field-related words and Google their meaning. Mentions of people with non-English names and last names are also more understandable, with a caption to follow.

Long-form content

Every video can be transformed into a variety of formats. This depends on the type of your video content and your goals. A transcription of a video can be edited and transformed into a blog post that contains concise takeaways from the podcast.

This goes beyond blog posts, as this textual information can also be used to create

  • Social media posts
  • Email pitches
  • Quotes
  • Infographics

If your podcasts are posted on your website, their transcription can help people discover your video content through search engines.

Personal notes

Many people enjoy using their notes app for daily or weekly reminders, shopping lists, or even for their intimate thoughts. When you are not in a position to sit down and write down what you want, you can use a speech-to-text app to make this process faster and more convenient.

Besides personal notes, this technology can be used for logs of various kinds. In healthcare, doctors can use such technology to track patient records.

Artists of different kinds and content creators can find this technology helpful as it can allow them to capture their ideas and thoughts on the go.

3 Key components of an excellent speech-to-text app

While there are many free speech-to-text apps, they usually don’t satisfy some of the key requirements that a paid one does. The common downsides of free software in this category are that it offers a limited amount of words, low accuracy, and usually requires a lot of editing.

1. Adapts to different environments

A good STT application will deliver you accurate transcription regardless of the environment that you are in. While it’s always expected for the voice or video recording to be as clean as possible, ideal conditions aren’t always available.

2. Understands different accents

The English language is present in every country in the world, and it’s certainly the most used language online. But this means that there is a growing number of non-native speakers that are self-taught English speakers.

This brings diversity to the language, and while their grammar is correct, their pronunciation might be hard to understand. An excellent STT software will be able to recognize different accents and accurately transcribe them.

3. Precision

When it comes to consumer-grade STT solutions, there probably won’t be one that’s 100% accurate anytime soon. However, you should aim for platforms that have over 85% of accuracy.

This is the most that you can ask for without having to spend a fortune on them or spending more hours editing than it would take a professional to do a transcription.

Speech recognition algorithms

Here are some of the commonly used speech recognition algorithms. They have their pros and cons and different approaches to solving certain problems.

1. Natural language processing

Natural language processing, or NLP, is a field of artificial intelligence that explores the ways through which humans and computers interact through language. This field combines linguistics with computer science, and AI examines large amounts of natural language data to deliver its results to the user.

This algorithm is commonly used on mobile phones, and the most popular system that uses it is Siri. GPS systems, digital assistants, and chatbots are some of the situations where this method is used. However, NLP is also very useful in optimizing business processes, improving onboarding for new employees, and helping companies increase productivity at their workplace.

2. Speaker diarization

This algorithm separates multiple speakers by their identity. Speaker diarization is very useful when you have a podcast with multiple people, and you want to separate their dialogues. In a broader field, this algorithm is used in call centers as it helps the management separate the customer from the agent.

Common patterns can then be recognized in the conversations and then resolved quicker in the future.

3. Neural networks

Neural networks are used in deep learning. Their method of learning is that they imitate the way that a human brain functions, thus the word Neural in the name of the method. The various layers of the human brain are represented by “nodes” in this method.

Each node consists of input and output, among other characteristics. Neural mapping is a very effective and precise method of deep learning. However, this method isn’t as time efficient as the other ones, as neural networks process vast amounts of data.

The speech-to-text transcription technology is rapidly advancing

Speech-to-text transcription technology has become increasingly popular. To hop on this trend, many corporations, such as Amazon and Apple, are developing their own systems to improve their virtual assistants and services.

The uses for this technology can be seen in sales, transportation, healthcare, and security industries, as well as in our everyday lives. Content creators and podcasters can use various transcription services to help them transcribe and translate their content.

Embracing STT technology as a content creator will help you stand out among the competition as it will allow you to create more content and attract a broader audience.

By Veljko Petrovic