Speech-to-text conversion of files is trendy today. Many businesses are using it as part of their marketing strategies, to improve SEO performance, expand their audience, for captioning and subtitling, and as a more convenient way of storing information. When you decide to transcribe your audio files, you might not know which alternative between human or machine transcription will yield high-quality work, especially when it’s your first transcription.
Comparing Human-Generated And Automated Transcriptions
With the increasing technological development, humans have engineered artificial intelligence to help them to perform tasks in minutes with utmost efficiency and correctness. However, this is not the case when it comes to transcription. In audio-to-text conversion, human-generated transcriptions remain the most reliable. While machine transcription might have the advantage of efficiency and speed, they fail at having cognitive intelligence. Here are more reasons why humans are better at transcription than speech-to-text software.
Noisy Audio
Sometimes you’ll do a recording in a noisy street or restaurant, resulting in a lot of background noise. Human beings can decipher the conversation to generate transcripts with minimal errors. On the other hand, machines have not learned how to differentiate relevant speech from background chatter.
Punctuation And Pauses
Human conversations sometimes pause when someone is collecting their thoughts or sipping coffee. While speech-to-text software is programmed with punctuation rules, they may not notice such pauses and may assume it’s the end of a sentence. Such errors can be annoying when you are reading a document. Conversely, human transcribers can quickly identify pauses to deliver correct transcripts.
Homonyms
Homonyms are words that mean different things but have the same spelling or pronunciation. Examples of homonyms are “horse” and “hoarse.” A human transcriptionist can listen to a file and allocate the right word depending on the context. Machines may not understand a conversation’s context, causing them to pick the wrong homonym. Using the incorrect word changes the document’s meaning, which can have undesirable repercussions in legal and medical fields.
Meaning And Relevance
A human transcriber can pick out what is relevant in an audio file and include it in the transcript. They make these judgments based on the context of the conversation. AI transcription applies its programming without understanding the message’s meaning or relevance. For example, it may not transcribe essential sounds like a pager calling or an ambulance’s siren.
Accents And Dialects
All languages have different dialects. Teaching machines all the types of dialects can take very long. When a transcription AI encounters a word it doesn’t know, it automatically tries to replace it with the closest word it has been programmed with. This changes a file’s message.
Transcription companies such as GoTranscript allocate projects to transcribers who are native language speakers. Therefore, they can differentiate dialects. Additionally, transcribers can research further when they don’t understand a word. They can also make out the different accents of speakers to deliver accurate transcripts.
Multiple Speakers
Speech recognition software has challenges transcribing conversations involving more than one person. It usually transcribes a conversation with multiple speakers as if it were from one person. Things become even more challenging if the speakers are using different languages. On the other hand, human transcribers apply intelligence to detect changes in voices, accents, and tones in a conversation.
Subject Matter Expertise
Industries such as medicine and legal demand the highest accuracy in transcripts. Human transcribers with professional training can apply their knowledge and years of experience transcribing for a particular industry. Since machines do not understand the industry jargon, they can not match up to the accuracy of professional human transcriptionists.
Final Thoughts
Human transcription is the key to getting high-quality and error-free results. While machines still need further programming to understand human languages, they still have a long way to go in understanding their many complexities. Hiring professional transcription services from industry leaders like GoTranscript guarantees you 99%+ accuracy in your transcripts. While using speech-to-text tools might seem cheap, they are likely to make errors that cost more in the long run.
