Similar to a sophisticated business computer programming language, audio transcription systems perform behind the scenes. They have the ability to streamline tasks, facilitate learning, and substantiate documentation – they generally perform unseen. As a result, they routinely support individuals to improve business process workflow, simplify content-sharing capabilities, and verify beneficial information. In a nutshell, they save organizations valuable time.
This article will provide an overview and guide to the audio transcription process, offering suggestions on when and how to use it, as well as examining the pros and cons of the different product variations in today's marketplace.
1. What is Audio Transcription?
Its most uncomplicated form is converting verbal and audio materials into text. As the name implies, audio transcription involves writing or transcribing, the contents of a recorded audio-visual file or recording. It is important to emphasize that the term audio-visual might relate to either an audio file or a video file. The term audio transcription might involve the audio transcription services within a video format.
2. What is Audio Transcription used for?
One of the most significant uses of audio transcription is producing an accurate written record of important events and providing machine-readable information for dissemination to key stakeholders. Audio transcription files are not readily available without the use of technical electronic devices. Once transcribed, the possible conceivable audience for this information is greatly expanded.
Furthermore, the audio content is not typically machine-readable, therefore search engine algorithms have difficulty assessing such content posted on a website. As a result, they cannot adequately index these files without a detailed metadata entry or a comprehensive transcription of the audio contents. Including transcriptions alongside the relevant audio files can build more end-user traffic to the site and effectively present the organization's key message.
3. How do you Transcribe Audio?
The task of transcribing audio files can occur in three modes:
A skilled human transcriber will listen to the audio, and manually type what was said into a file.
A transcriber can use software programs that will reduce the audio speed. This process will enable the transcriber to listen and type the contents, using specialized headsets and foot pedals. These pedals can stop and start the audio during playback. Software programs such as these can remarkably improve the accuracy and efficiency of the audio transcripted outcome.
Lastly, audio files can be transcribed automatically using a specialized software program or an online web-based artificial intelligence platform. This process is gaining more popularity and will eventually dominate the audio transcription market.
It is important to note that all three methods vary in their accuracy and sophistication output.
In particular, the software requires input from high-quality audio transcription files and non-accented American English to achieve an accuracy rating of 85 percent or greater. Using machine learning algorithms, certain software programs can improve their accuracy ratings over time. By utilizing machine learning, these software programs can increase their precision transcripts with repeated exposure to a speaker's particular accent over time – the very essence of what machine learning can achieve with software systems.
4. What is Speech Recognition?
The audio transcription discussion now brings us to the important concept of speech recognition. Quite simply, speech recognition is a technique for translating speech to text via artificial intelligence means. For example, speech recognition software can convert a live or recorded audio session of a spoken language into text almost instantaneously.
5. What is the difference between Speech Recognition and Voice Recognition?
There is a key distinction between speech recognition and voice recognition methods to transcribe audio. And that is for any given audio where an articulated and spoken language can be heard, speech recognition software will identify the words used. In contrast, voice recognition software will identify the speaker only.
Voice recognition is typically limited as a security measure only for unlocking electronic devices or security doors using one's speech or a specific phrase. Therefore it can be personalized. Speech and voice recognition are occasionally used interchangeably to indicate the same notion (i.e., converting speech to text), but there are both subtle and significant differences between the two.
6. SEO Benefits
Audio transcriptions via speech recognition play a primary role in search engine optimization because search engines do not index video or audio files. By converting this content type into text, transcribed audio files expand their searchability. For example, podcast transcription can assist people in locating specific podcast series or episodes relevant to their initial search query. Additionally, academics and business leaders can transcribe seminar presentations or conferences to increase exposure to their discoveries and conclusions. Webinars, video logs (or vlogs), lectures and speeches, and how-to instructional videos are other reference materials that acquire SEO benefits by being converted into audio transcriptions.
7. Key Industries that use Speech Recognition
Speech recognition for audio transcription is used in an assorted array of industries, including education, healthcare, legal, law enforcement, entertainment, and of course, business.
The two main functions of speech recognition applications are speech-to-text and voice command operations. They add efficiency and effectiveness in virtually any profession, particularly those that deal in computer-related activities.
8. The Importance of Speech Recognition with Audio Transcription
There are two basic benefits of utilizing speech recognition applications or services:
The time savings they provide, and
The higher accessibility to key stakeholders
Working time conservation and overall efficiency is mostly why speech recognition capabilities have been adopted within numerous business industries and sectors.
Speech recognition is considered mutually advantageous for both businesses and their employees because it leads to increased work automation and higher efficiency.
Speech recognition offers improved accessibility as its benefits are used without a mouse or keyboard. This notion keenly illustrates speech technology as even more efficient than traditional audio transcription data entry methods and practices.
9. Most popular Speech Recognition Software
The most popular speech recognition software tools are currently free to obtain and use. Take Google's speech-to-text tool, which operates its speech-to-text services on both Mac and Windows operating systems. Virtual assistants on smartphones are all built-in high-end features with elevated precision and functionality.
It should be noted that there are limitations to these free speech recognition options. But they are convenient and usually do a satisfactory job when transcribing audio files.
10. Paid Speech Recognition Software
Some of the most prominent names in the technology sector monopolize the free speech recognition software, and they are always delivering new releases. Nevertheless, free software is not always best suited for professional audio transcription tasks.
Vendor Description has an all-in-one editor that enables easy editing with all uploaded media. It can also record directly within the Descrip tool, which can instantly transcribe audio files into text. Customers have reported that audio transcriptions with Descript are frequently fast and accurate.
Nuance Communications is probably the largest name in the paid speech recognition market with its range of Dragon Software Transcription products. These tools have been created and developed for the previously cited industries (legal, healthcare, and law enforcement).
Also, there are two other major speech recognition and transcription vendors within the healthcare industry: 3M and Dolbey.
Amazon's commercial speech recognition engine – Amazon Transcribe – has its foundations built with a specific pricing model based on the number of seconds of audio transcribed. Basically, it is a “pay only for what you use” business model. This business offering is ideal for those customers who need extensive quantities of audio to be transcribed but do not necessarily require transcription services all the time.
Amazon also has expanded the Transcribe service software explicitly for the healthcare industry, in the form of their Amazon Transcribe Medical software offering.
The IBM Watson software solution is an exceptionally accurate speech recognition platform designed for commercial enterprises. IBM Watson can be used for straightforward speech-to-text transcription services, but it can also transcribe audio calls from call centers or be used as the speech virtual assistant engine on support calls.