How to Transcribe Audio to Text: A Guide to Audio Transcription and Speech Recognition

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Robert Koch

I write about AI, SEO, Tech, and Innovation. Led by curiosity, I stay ahead of AI advancements. I aim for clarity and understand the necessity of change, taking guidance from Shaw: 'Progress is impossible without change,' and living by Welch's words: 'Change before you have to'.

Transcribe audio to text can be a valuable process for creating accurate records of conversations, tracking and transcribing speeches, and more.

In this guide, we will discuss the benefits of audio transcription, its use cases, speech to text, AI transcription and human transcription and speech recognition. By learning about these topics, you’ll have a better understanding of how they work and how you can put them to use in your own business or personal life.

Table of Contents

• What is Audio to Text Transcribing?
• What are the different types of transcription?
• Types of Transcription files
• How long does it take to transcribe audio into a text file?
• Etymology
• What is not an Audio Transcription?
• History of Audio Transcription
• Use Cases of Audio Transcription
• Benefits of Transcribing Audio to Text
• 7 Reasons for the Conversion of Voice to Text
• What are the main ways to convert audio to text?
• How to get started with transcription?
• What is Speech Recognition and how can it be used to transcribe audio to text?
• Training Data for Speech Recognition Systems
• Audio Datasets & Voice Datasets for Speech Recognition training by clickworker
• Audio to Text Transcription Services using Speech Recognition
• How Speech to Text will influence Transcription in the Future
• Conclusion
• FAQs

What is Audio to Text Transcribing

Audio transcribing is the process of converting an audio or video recording into text. This can be done manually, with the help of transcription software, or automatically using technology. In many cases, it is used to create a transcript of a meeting, interview, or lecture.

Manual transcription is the process of typing outspoken words as they are heard. While this method can be time-consuming and inaccurate, it does offer some benefits such as affordability and accuracy.

Technology-assisted transcription uses software to convert audio files into text format. This type of transcription offers several advantages over manual transcription including speed, accuracy, and cost-effectiveness. Speech recognition technology is becoming more common and helps create transcriptions automatically.

Types of Audio Transcriptions

Audio transcription could be classified into various types depending on various factors. Based on when the audio is transcribed, you can classify it as either live audio or recorded audio transcription

Live Audio Transcription

As mentioned earlier, historically, audio transcription was used to transcribe real-time human speech to text. This means the scribe actively listened to and wrote the speech in real-time, just as the speech was made. This kind of live audio transcription is still carried out during several events and occasions, such as during court proceedings, classroom lectures while writing down meeting minutes, and so on.

Recorded Audio Transcription

During a recorded audio transcription, the scribe uses a recorded audio or audiovisual file to listen to and transcribe the content into text format. While both analog and digital recordings can be used, nowadays, audio is mostly shared in the form of digital files.

Based on the method used, it can be termed manual or automated audio transcription.

• Manual

Manual audio transcription is carried out by a human scribe who actively listens to the audio or audiovisual content and transcribes it into a textual format.

The scribe could use different techniques and tools to transcribe the audio. But it involves their active participation and careful dissemination of the input audio.

• Automated

Automated audio transcriptions are carried out with the help of an automated software tool without active participation by a scribe. We can easily convert audio files to corresponding textual data using advanced technology such as AI-based speech-to-text conversion applications. Many online services and software tools provide both live and recorded audio transcriptions. These tools provide quicker solutions but may not always have the same accuracy as the manual transcription process.

Based on the type of processing carried out while transcription, it can be classified into the following types:

• Verbatim transcription

Verbatim transcription is the strictest type of transcription where everything the speaker says is all transcribed, including non-words, fillers, and any other type of sounds made by the speaker. It includes verbal and non-verbal communication in the audio, including the background noises. Verbatim transcription, more accurate about the context and surrounding information, is used in complex scenarios such as legal work, movies, commercials, etc.

• Edited transcription

Edited transcription is a lenient form of verbatim transcription where the words spoken are all preserved just as the speakers speak. But unnecessary non-verbal information and non-words are edited to make for a cleaner and easy-to-read transcript. It is the most commonly used form of transcription and is applied in many cases, such as publishing conference recordings, public speeches, seminars, and so on.

• Intelligent transcription

Intelligent transcription focuses on delivering the meaning behind the audio content and thus allows the transcribers more flexibility. Transcribers may edit or rephrase sentences to make the transition more readable, concise, and easy to follow. Repetitive sentences, redundant words, irrelevant content, and bad grammar in the original speech may all be rectified or removed in the output transcript.

This type of transcription is used in cases where legibility is preferred, such as transcribing a business meeting, classroom lectures, interviews, and so on. The resulting documents are easy to understand and share among the stakeholders.

• Phonetic transcription

A phonetic transcription is a specialized form of transcription where the transcription notes how the speech is delivered. Pronunciation, intonation, tone of the content, and the various sounds included in the audio are all annotated in the transcript.

Hence phonetic transcriptions may require additional information to decipher the transcript and are carried out by experienced scribes who can infer the subtle differences in sounds and are skilled in the phonetic alphabets. This type of transcription is often used for analysis purposes in academic or expert linguistic projects.

Types of Transcription files

There are three main types of transcription files: TXT, WORD, and HTML.

The TXT format is the most basic type of file, and it’s just a text document with no formatting. The WORD format is similar to the TXT format, but it includes basic formatting like bolding and italics. The HTML format is more complex than the other two formats, and it allows you to create webpages with headings, paragraphs, and lists.

The SRT file format is specifically designed for videos, as it provides a time-stamped transcript with natural language processing capabilities. This means that the transcriptionist can easily identify when specific words are spoken in the video.

How long does it take to transcribe audio into a text file?

The process of audio to text transcription is dependent on the quality and complexity of the original recording. If the audio is clear and concise, it will take less time, to transcribe audio to text, than if the audio is muffled or contains a lot of background noise.

Self-transcribing can be very time consuming, depending on the length of your audio and your experience with transcribing. Generally, the more experienced you are as a transcriber, the faster you will be able to complete a transcript.

However, even an expert may take hours upon hours to transcribe a long recording accurately. The best way to reduce transcription time is by using automatic transcription software. This software saves time by doing all or most of the work for you; however, it is not 100% accurate.

Proofreading after automatic transcription can take additional time but results in a high-quality transcript that meets your needs.

Etymology

The term ‘Audio transcription’ is a combination of two words: audio and transcription. Audio is particularly used to refer to recorded sound or sound signal transmissions and is derived from the Latin word, ‘audire’, which means ‘to hear’.

Transcription is derived from another Latin word ‘transcribere’, which means to copy, write, or transfer writing.

Combining these two words archives the meaning of transferring audio to a written form which is exactly what audio transcription means.

What is not an Audio Transcription?

Audio transcription could sometimes be mistaken as either translation or as transliteration. It is important to note the difference between these three closely related terms.

Translation vs. Transcription

The difference between translation and transcription is quite straightforward.

While audio transcription converts audio to a written format, translation changes input audio or text to a different language. Translation involves two languages, whereas transcription is strictly limited to the source language.

Another notable difference is that transcription applies only to speech or audio content, whereas translation is applied to written and spoken content.

Transliteration vs. Transcription

Transliteration is the process of converting written information from one script to another. But transcription converts speech into writing. But there are some instances when transcription and transliteration could be mistaken to be the same. For instance, when you try to transcribe audio spoken in a foreign language to a script of a different language, it might seem like both transcription and transliteration are being carried out. But there is a sharp difference between the two processes.

Transcription converts the speech into either English or a foreign language, and the output has actual words from the corresponding language. Whereas in transliteration, the output will be in the script you choose but might not make sense in the language it is written. It is like writing Russian using the Latin script. 

Here is an example that demonstrates the differences between these three processes:

• Translation:

Consider an input word, ‘Hello’

Translation to French: Bonjour

• Transliteration:

Input word: नमस्ते

Transliterating to English: namaste

• Transcription:

Unlike transliteration and translation, transcription is only applied when audio input is involved.

History of Audio Transcription

Transcription was used as a form of documentation as early as 3400 BCE. Important information, such as history, stories, law, and accounting details, were recorded by scribes onto various written media such as tablets, papyrus scrolls, and more. The ancient hieroglyphics found in the Egyptian pyramids and tombs are all a form of audio transcription where the information recited by someone was recorded by a scribe.

Transcription was also used by religious leaders and scholars to pass down oral traditions and scientific findings to the next generation. Transcription existed and flourished across various civilizations all over the globe as a way to pass information down from one generation to another. The job of a scribe requires extensive education and practice to master their scripting skills.

With the invention of the printing press in 1439, transcription services started to evolve. People could access printed texts more, and the role of scribes was solely relegated to creating first copies or recording audio information. Many scribes adapted shorthand techniques to note down oral information at a rapid pace. This change in transcription practices gave rise to stenography which is still in use today.

The next big step in transcription came with the invention of the typewriter in 1867, followed by computers with their word processing applications, which made transcription much faster and more efficient.

And currently, advanced AI applications have also made it possible to transcribe audio information automatically without needing a human scribe.

Use Cases of Audio Transcription

There are many different use cases for audio transcription. One of the first use cases for speech recognition and transcription was transcribing lectures in schools and businesses so that other people could enjoy or consume them. Depending on the application, speech recognition and audio transcription can be used for a plethora of things including quality control, commenting on social media, or easily listening to public speaking in person. Some of the most common include:

• Conference Calls: When reviewing conference call recordings, it’s important to have a written transcript to reference. Audio transcription services can provide accurate transcripts of these calls in a timely manner.
• Interview Transcription: Interviews need to be accurately transcribed for review by hiring managers or legal teams. Professional transcription services can ensure accuracy and timeliness when providing these transcripts.
• Medical Data Transcription: Physicians and other medical professionals often need to quickly access patient data, which may be available in audio form. Medical data transcription services can convert this audio data into easily-readable text documents quickly and accurately.
• Transcribing Podcasts: Podcasters often want to create written content from their spoken word shows. Transcribing podcasts with an audio transcription service can help make this process easy and efficient.
• Video to Text Conversion: Many businesses want the ability to search through videos for specific information, but find it difficult because the video footage contains no text overlayed on top of it. Converting video footage into text files makes this information easily searchable.
• Mp3 to Text Conversion: Audio files are often converted to text formats so that they can be more easily read and searched. This is a common practice with mp3 audio files, as they are typically smaller in size than video or audio files in other formats.
• Subtitle Generation: When videos are uploaded online, it’s often necessary to generate subtitles for them in different languages. Transcribing the audio of these videos into text form makes this process much easier and faster.
• Speech and Voice Recognition: Speech recognition software is becoming more and more prevalent in today’s society. By transcribing spoken words into text form, this software can become even more accurate and efficient.

Tip:

Modern speech recognition systems need human input in the form of datasets.

Audio Datasets

Benefits of Transcribing Audio to Text

There are many benefits to transcribing audio to text. The most obvious benefit is that it provides a better user experience. When people can read what they’re hearing, they’re more likely to stay on your page or continue listening to your podcast. Transcribing also increases your chances of being quoted and credited for the content, and it helps improve SEO ranking factors.

Transcription is an important legal requirement for many businesses and organizations, making it accessible for everyone in the US based on disability laws like ADA or Section 504/508 of the Rehabilitation Act. Most transcription services offer transcripts that are compliant with Level A accessibility standards, which ensure that everyone has equal access to the content.

Audio transcriptions offer new options like reach and accessibility to content while offering a cost-effective way to make these materials accessible. Additionally, transcribing audio files is a great way to get better at listening, comprehension, and note-taking-skills that are essential in any profession.

We are encountering automatic transcriptions more and more frequently on the web. For example, on YouTube:

• When the sound is turned off, video previews sometimes show the spoken text.
• The “Show transcript” function can easily be switched on by clicking on the three dots at the bottom of a video.

Content for the Internet is increasingly presented in the form of videos and podcasts. That’s why the option of audio transcription is becoming more important. There are many arguments to rely more on this conversion from audio to text, especially in e-commerce. Speech to Text software uses artificial intelligence to create accurate transcriptions. This means that the accuracy of transcribing will be very high and there will be little or no need for manual editing. As such, businesses can save both time and money with this technology.

What are the main ways to convert audio to text?

There are three main ways to convert audio to text: DIY, automatic software and human services.

• DIY transcription is a process where you use software or online tools to convert the audio file into text yourself. This can be a great option if you only have a few files to transcribe or if you want more control over the final product. However, it can also be time-consuming and challenging if you’re not familiar with the tools involved.
• Automatic transcription software uses algorithms to automatically convert an audio file into text. This can be a quick and easy way to get your transcripts done, but the results may not always be accurate. It’s important to check the output of these programs against the original audio file to make sure there are no errors.
• Human services are offered by companies who employ people specifically trained in speech recognition and transcription. These services tend to be more expensive than DIY or automatic solutions, but they often provide high-quality transcripts that are accurate and easy to read.

DIY: Self Transcription of Audio Files

Transcribing audio files can be a difficult and time-consuming task. However, it is important to do if you want to create an accurate transcript of the audio content. Here are some tips for manually transcribing your audio files:

• Listen to the entire audio file before you transcribe audio to text. Make sure you take the time to listen and type out each word. This may seem like an obvious step, but it’s easy to miss words or make mistakes if you’re not paying attention.
• Edit your transcript before it becomes a book or blog post. This will help you catch any missing words, errors, or inaccuracies.
• Listen to your audio content again after transcribing it. This will help you verify that the transcription is accurate and free of errors.
• Use a transcription editor software, such as Happy Scribe’s free online transcription software, which will make the process easier.
• Save your work often so that you don’t lose any changes made

Automatic Transcription Software powered by AI Audio Transcription

This type of software is easy and affordable to use, but it can be inaccurate when there are heavy accents or complex content. If you’re not satisfied with the auto-transcription process, you can always check for errors manually. Make sure you review your final transcript for mistakes before publishing it online or sharing it with others in case there are typos which will confuse people and cause issues in search results and elsewhere in their content marketing strategy.

Human Transcription Services

Human transcription services are a great choice for producing clear, accurate transcripts. They offer a number of benefits over machine transcription:

• Better accuracy – human transcribers produce more accurate transcripts than machines, thanks to their ability to interpret nuances in speech.
• Faster turnaround – human transcription is often faster than machine transcription, meaning you’ll get your transcript sooner.
• Greater flexibility – human transcription services can handle a wider range of audio files than machine transcription tools. This means they can work with more file formats and be used for a wider range of purposes.

It’s best to provide your transcriber with as much relevant information as possible so they can create the most accurate transcript possible. This includes speaker names, topic titles, and any other relevant information about the audio file you’re sending them. Speech recognition and human transcription are combined in order to produce transcripts at outstanding quality and accuracy.

Transcribe Audio to Text: How to get started?

At some point, you’re likely to have audio that needs transcribing. Whether it is interviews or voicemails from a phone call, there will always be that one project where the audio is the key. It’s not impossible to transcribe audio to text, but it can be a daunting task that requires some knowledge and skill. The process of transcribing audio to text can be broken down into three steps: recording the audio, converting the file format and then using software to convert it into written text.

Invest in a Good Transcription Software

When it comes to transcription, there are a few things you need to consider:

• The quality of the audio for each product.
• How much time is needed to convert files into text documents?
• How many users and projects will be supported by the software?
• Turn-around time for transcription software is one of the most vital features to look for when choosing audio to text converter. Real-time transcriptions are a fast and accurate option, which eliminates the need to wait or miss important details during meetings or lectures.
• Voice recognition technology can identify your voice amongst different voices and accents. Highlighting allows you to identify important sections in the document. This function allows you to have a better understanding of the concerned subject. This feature also allows those who have access to your file view transcriptions on their device.
• Keeping organized

The software allows for easy integration with a variety of apps such as Google Drive, Dropbox, iCloud etc., as well as meeting features like automatic joining and transcription that can be done under one source!

Use an Automatic Transcription Service

A machine transcribed conversation can be created without relying on a human to type out the words. Transcription services have become more prevalent in recent years, due to improvements in technology and improvement of search engine algorithms that can’t process human language in real-time.

What is Speech Recognition and how can it be used to transcribe audio to text

The process of converting speech into text is computer-aided and is called speech recognition software. Speech recognition allows users to dictate their thoughts and ideas, which can then be transcribed as text by a computer. Speech recognition is primarily used in the field of natural language processing, which is a branch of computing that deals with artificial intelligence as well as knowledge representation.

Speech recognition software has been around since the 1960s, but it was not until recently that improvements in technology have made this service more viable and widely used. Speech to Text software uses artificial intelligence to create accurate transcriptions. This means that the accuracy of the transcription will be very high and there will be little or no need for manual editing. As such, businesses can save both time and money with this technology.

The difference between Automatic and Manual Transcription

Manual transcription is the process of transcribing an audio recording by typing what is said word-for-word. This can be a time consuming process, and it’s often difficult to decipher words when there is noise in the recording or when the speaker has a heavy accent.

Automatic transcription of speech software can transcribe audio recordings in many languages and accents. This saves time that would otherwise be spent manually transcribing recordings. Automatic speech recognition technology works by translating spoken words into text using natural language processing algorithms. These algorithms are designed to understand the structure and grammar of human language. Errors are detected by checking the final transcript file against the original audio recording. The main advantage of automatic speech to text transcription is time saved, as the user no longer needs to manually transcribe files. This method may not produce accurate results if your content includes heavy accents or complex audio elements.

What makes Automatic Speech to Text Transcription possible?

There are a few things that make automatic speech to text transcription possible. First, the advancement of artificial intelligence and machine learning algorithms has made it easier for computers to understand spoken language. Additionally, the growth of voice recognition software has made it easier for computers to convert spoken words into written text. Finally, the increase in demand for transcriptions services has helped create better tools and workflows for making transcripts more accurate.

Speech Recognition Systems and Tools

A new digital era is upon us, and the way we communicate has changed. The old-fashioned telephone line is now a relic of technological history while even in busy cities like New York City or London, people have begun to use video-conferencing and online meetings. One of the most advanced technologies in this digital era is voice recognition software which has been used as an effective tool for individuals.

Transcription of speech technology has come a long way and is now used in various industries. It’s made automatic speech to text transcription possible. Microsoft, Happy Scribe, and other companies have developed algorithms that can convert speech in seconds or even real-time. Automatic speech to text transcription is possible with the use of voice recognition software and advanced speech processing. The accuracy rate for automatic speech to text transcription is not 100% perfect, which is why it’s combined with a human transcription service.

Training Data for Speech Recognition Systems

The key to a good speech recognition system is training data. The more data you have, the better your system will be at recognizing different voices and accents. That’s why it’s important to get as many people as possible to use your speech recognition system so that it can learn from as many different voices as possible.

There are also online tools that let you upload your audio files and automatically receive a transcript of the recording. This can be helpful for editing purposes, since you can see exactly what was said in the recording. Speech to text is usually accurate within 10% of the original audio, but it may vary depending on the quality of the recording and the accuracy of the transcription tool.

Audio Datasets & Voice Datasets for Speech Recognition training by clickworker

Prompt delivery of large quantities of high-quality, human-generated voice data for speech recognition system optimization, as well as 4.5 million global Clickworkers for the creation of your recording and diction dataset.

Each person’s voice and speech patterns are unique. They differ in intonation, pace, pronunciation and dialect. These complexities complicate the development of the automated speech recognition systems. A reliable speech recognition system must be trained with a high volume of high-quality audio datasets and datasets of different dialects and then developed by a diverse group of individuals to cover the range of human language nuances.

High-performance speech recognition systems need large sets of voice data to work and rely heavily on human-made recordings. An international pool of Clickworkers, provides authentic audio recordings while also doing transcriptions in a variety of languages. In order for the transcriptions to be accurate, Clickworkers must carefully follow a checklist before submitting it for processing.

In speech recognition systems, it is necessary for the computer to usually “speak” by matching up mouth movements with vocalized sounds. This allows the computer “voice” to match text in a given audio file with its correct corresponding letter, word or phrase of text. Since it is challenging and often impossible for any human to decode these sound files on their own, we are able to take care of this difficult step in our system and only make this data available to your speech recognition system that needs it.

Analyses can included, for example, the emotional tone of a voice, as well as what is said in terms of subject matter, and the quality of sound on an audio file. An analysis of this data provides your system with first-rate data that can be used for human interaction via machine intelligence.

Audio to Text Transcription Services using Speech Recognition

Many companies will transcribe audio files for you, but they tend to be expensive. Some of them charge by the minute and others charge a flat fee per file. If you have a lot of files to transcribe, you can use speech recognition software and save yourself some money.

The most common type of audio transcription is done by speech recognition software like Dragon Naturally Speaking, Microsoft Cortana, or Apple’s Siri. It has many benefits including being relatively inexpensive and fast. Software can be purchased for a one-time fee or monthly subscription. You can also sign up to use the software through an online service, which will give you access to many different types of audio files and a variety of different languages.

The software works by listening to the audio file and then converting it into text using a speech recognition engine. The accuracy will vary depending on how clear the recording is, how fast the speaker is talking, and other factors. If you are having trouble with accuracy, try to find a quiet place to record your audio.

There are many different types of software that can transcribe audio to text. The most common are desktop applications, which you download and install on your computer. Some of these programs are free, such as the open source software ” Audacity ,” but many have a cost associated with them.

The most popular web-based speech recognition is Google Docs, which can be used to create documents and spreadsheets using your voice. You can also use it to create and edit presentations. It is free to use, but you need a Gmail account in order to take advantage of it. You can still use the program if you don’t have a Gmail account, but you’ll be limited to creating documents that are less than 10 MB. This web-based tool is also available for mobile devices, so you can make edits on the go.

How Speech to Text will influence Transcription in the Future

Speech recognition technology is becoming more and more popular, and it is changing the way transcription is done. With speech recognition, you can simply speak into a microphone and your words will be automatically transcribed. This technology has many advantages over traditional transcription methods.

First of all, transcription of speech is much faster than traditional transcription methods. You can easily dictate a whole document in just a few minutes. Additionally, speech recognition is very accurate, so you don’t have to worry about errors or mistakes. Finally, speech recognition is available in many different languages, so you can use it no matter what your native language is.

Overall, speech recognition technology is changing the face of transcription and making it easier than ever before to get your words down on paper.

Transcribe Audio to Text: Conclusion

Audio transcription offers companies many opportunities to increase visibility and user experience. Above all, audio transcription can be used to increase the reach of content. A prerequisite for effective transcription work is powerful transcription software. The program of choice should be easy to use, deliver accurate results, and integrate well with existing structures. To be on the safe side, fully automated transcriptions should be checked by humans at the end before being published as new content.

We hope you enjoyed this guide on transcription! As you can see, there are many benefits to transcribing audio to text. Whether you need to transcribe interviews, lectures, or meetings, there is a transcription method that will work for you.