An audio-to-text converter is a transcription software that automatically recognizes speech and transcribes what is being said into its equivalent written format. Traditionally, a human would listen to the audio file and type it into a text file to repurpose the spoken content for different media. But now, using artificial intelligence, computers can easily convert audio to text in a short time and make the content usable for different purposes like search, subtitles, and insights.An audio-to-text converter is a transcription software that automatically recognizes speech and transcribes what is being said into its equivalent written format. Traditionally, a human would listen to the audio file and type it into a text file to repurpose the spoken content for different media. But now, using artificial intelligence, computers can easily convert audio to text in a short time and make the content usable for different purposes like search, subtitles, and insights.
What are some use cases for audio to text converters?
The audio-to-text converter reduces transcription time, increases efficiency and productivity, and improves the accessibility of digital media. The following are some reasons why companies use software to convert audio and video files to text.
Improve content accessibility and reach
Video content can reach a wider audience and improve engagement if you add subtitles. Non-native English speakers can understand such videos more easily. Moreover, social media platforms actively support video media feeds on mute because many internet users prefer to watch short videos silently while reading subtitles.
A video file can be challenging to transcribe because you might need to spend hours watching video footage and transcribing manually. Audio-to-text converters make the process easier and free up editing time so you can create more content.
Extract actionable insights
Transcription enables you to extract insights from information trapped in audio and video files. For example, you can convert customer reviews, customer calls and interviews into digital data. You can record repetitive information or common onboarding processes as an audio file and then transcribe them into a document. For example, Intuit, a call center company uses audio-to-text converter software to automatically transcribe audio from calls and analyze the text for call metrics and center performance.
Generate content faster
There are numerous types of marketing channels that your audiences might use. Companies today create podcasts, articles, images, video content, and social media to engage with customers. Converting audio to text makes it more efficient to create a range of content from the same idea. For example, content creators can record audio for podcast interviews with industry experts, then transcribe the audio files to text and reuse the content for an article or white paper.
Automate note taking
From meetings to long lectures, speeches, and training sessions, you often need to revisit spoken content at a later stage. Instead of wasting work hours by transcribing audio files manually, you can convert audio to text in just a few minutes with software, even while you record. The resulting text document is also easy to refer to, unlike audio files that you have to pause and play repeatedly. You can save time and resources by reducing paper documentation like clinical documentation, notes, etc.
What are the benefits of using audio-to-text converters?
Audio-to-text converters bring many benefits in analytics and comprehensive documentation. Here are some examples below.
Searchable media content
It is challenging to classify and sort data in archives that have a large number of video and audio files. By transcribing audio to text, you can use this data archive for reference and research. For example, Audioburst uses automatic transcription software to create an audio recording repository of its talk shows with content that anyone can search and share.
Faster documentation
Documentation can be slow if you convert audio to text notes manually. For example, medical doctors record clinical conversations, but it can take a long time to convert the large volumes of dictated text into documents. Instead, you can use automated audio-to-text transcription to convert your audio file into a document on the fly.
Secure customer data
Automatic audio-to-text transcription can secure customer data with greater accuracy than manual transcription. You can set rules in the system to automatically redact sensitive personal information, remove profanity, or scramble private numbers while converting audio files to text.
How do audio-to-text converters work?
Automatic transcription software recognizes speech by using machine learning (ML) and artificial intelligence (AI). Machine learning is the technology that trains computers in speech recognition by storing and analyzing a very high volume of speech data. Audio-to-text converters give accurate results because they can compare recorded speech patterns to this massive database. When you upload audio files, the converter analyzes them by using two main components.
Acoustic component
The acoustic component is the software that converts the audio file into a sequence of acoustic units. Acoustic units are the digital signals that represent sound waves or the sound vibrations you make when you talk.
Acoustic speech recognition technology matches the acoustic units to sounds that make up the human language, called phonemes. For example, English has 44 phonemes that combine to form all the words in the language. You can use phonemes to automatically convert audio to text in many languages.
Linguistic component
While the acoustic component hears the word, the linguistic component understands and spells it. For example, many words in English sound the same but are spelled differently. The words to, two, and too all sound the same, but a person or computer that is transcribing audio must understand them in context.
The linguistic component analyzes all the preceding words and their relationships to estimate which word is likely to come next. It then converts the sequence of acoustic units into words, sentences, and paragraphs that make sense to humans. This speech recognition technology is similar to the auto-suggest function in your smartphone that automatically suggests words when you type text.
