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What Impacts the Quality of Automated Transcriptions?
admin
06/07/2022
Artificial intelligence is at the heart of the technology utilized in automated transcriptions. This is because automatic speech-to-text recognition programs are used in this type of transcribing. Both live and recorded audio files can be transcribed using software that are readily available to anyone with a computer, smartphone, or tablet and an internet connection. Business professionals and lawyers use recording devices or even their smartphones to dictate their messages. And for these professionals, it is usually a cumbersome task to manually transcribe these recordings by themselves. That is when they may employ the use of automated transcription generation software and/or services. However, there are certain factors that tend to impact the quality of automated transcriptions. The quality of an automated transcript is affected by several factors, some are more important than others but depending on your needs, different aspects should be addressed.
This article shall attempt to provide an insight into what are the factors that impact the quality of automated transcription and how.
1. Audio Quality:
If your audio is unclear, the automatic transcription of your audio file will also reflect that. One way to increase the chances of a clearer transcript is to have a professional record your message or use a high-quality microphone for recording. Another way you can increase the odds of having an accurate transcript is by including timestamps to indicate where pauses and breaks happen during recording. This will make it earlier for any person manually reviewing the transcription to pinpoint the areas where errors were made and to correct them.
An important aspect of preparing your audio file is to make sure that it is of high quality, this will greatly benefit the end-user. Some things that can affect the quality of audio files include frequency and dynamics. Frequency is how much detail you hear in a recording and Dynamics is how loud and soft it is. The microphone equipment should also be high quality, minimally having some sort of polar pattern: omnidirectional or bi-directional.
2. Different Accents:
Many of the people who use automated transcription will be using it for a variety of purposes. When working on any projects that might need to get transcribed, it is important to consider how different accents might affect their transcription performance and accuracy.
Word stress is when the stress of a word is placed on one syllable. In English, for example, the word “receipt” is stressed on the second syllable while “accept” is stressed on the first syllable. When a speaker has a strong accent in their native language, it often leads to an incorrect perception of where word stress occurs during speech. This can lead to misaligned word boundaries, or having letters of words swapped out with incorrect ones as artificial intelligence is not yet equipped with the ability to decipher the myriad accents that exist resulting in incorrect automated transcripts.
3. Background Sound:
Background noise in an audio file refers to pre-existing noise or ambient noises. One of the most obvious and typical examples of this is an interview in which two or more people are speaking to each other at length without any edits being made in between their stories, interrupted by incidental sounds such as birds chirping or cars passing by. Any such recording is likely to have multiple noises overlaid on top of each other.
It is, therefore, imperative to clean up these recordings before they are inputted into any automated transcription generators. If we try to feed in a recording of an interview with a lot of background noise directly into a software that is designed to ideally work with clean recordings, then this might result in the generation of an inaccurate or incomplete transcription.
4. Talking Speed:
One of the best ways to improve transcription accuracy is by adjusting the speaker’s speed.
Slower talk usually makes for a more accurate transcript as compared to those who talk faster. When one speaks at a slower pace, one is also articulating more clearly, which then results in a much higher quality speech recognition and thus affecting the overall accuracy of the final automated transcription.
It may not be easy for all speakers to talk at a slower rate for multiple reasons, however, slowing one’s speed of taking is one of the fastest and easiest ways to ensure the generation of an accurate automated transcript as the AI technology will be able to decipher the audio recordings faster and more accurately.
5. Data Representation:
Automated transcription can be unreliable when voice-recognition software has an inaccurate understanding or an insufficient level of input data representations. Automated transcription software cannot discern if a certain text should come before or after a detected word. If the transcription software detects a word incorrectly, this error can create a corrupt character sequence that affects all following characters until it is corrected thus leading to the creation of an inaccurate automated transcription.
Conclusion:
There is no denying the fact that AI technology today is highly advanced and It will only further change and improve with the dynamics of the world. Automated transcription programs are speedily evolving to improve speech-to-text algorithms as more users adopt this technology.
Background noise and numerous speakers talking over each other are two examples of issues that can affect the accuracy of machine-generated transcripts. Machine learning still has a long way to go before we see them evolve to be totally error-free, but there are certain things users can do to increase the accuracy of their automated transcripts.
One way to correct errors within an inaccurate automated transcript is for the user to manually compare the audio recording with the auto-generated text and correct the inconsistencies themselves. This can an arduous and time-consuming task for anyone to undertake. In instances like these, users can choose to employ the use of services like Ant Datagain which not only leverages the best in industry automated speech-to-text technology but also offer manual transcription services, where our expert transcriptionists undertake the task of cleaning up any inaccuracies within the automated transcript. This way, the user is free to focus on more important tasks.
Although artificial intelligence (AI) speech-to-text technology isn’t perfect, it’s improving all the time, and ANT Datagain is no exception to this trend of growth. With our extensive experience, we are able to understand the industry trends, and how to leverage the best industry practices and technological developments, which helps us deliver a consist quality product.
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