Transcription is the process of transcribing spoken words into written form. This can include the transcription of lectures, conversations, speeches, interviews, podcasts, videos, audio recordings and more. Transcription is often used in interviews.
How does A.I.-based interview transcription work?
A.I.-based automatic interview transcription, also known as automatic transcription or automated transcription, is the process of transcribing audio or video interviews using A.I. algorithms. It uses techniques such as automatic natural language processing (NLP) and speech recognition to translate recorded speech into written text.
The following are the general steps of A.I. -based automatic transcription:
Pre-processing: The automatic transcription system analyzes the recording to determine parameters such as sample rate, channel, and bit rate.
Segmentation: The system divides the recording into segments for further analysis.
Speech recognition: The system uses speech recognition algorithms to convert audio segments into words and phrases.
Syntactic analysis: The system uses automatic NLP techniques to analyse the syntax of sentences and identify key words.
Transcript generation: The system uses the information obtained to generate a written transcript of the recording.
Verification: The system can use automatic correction to correct any errors in the transcription.
How does human transcription work?
Human transcription of interviews is the process of transcribing spoken words into written form. Human interview transcription can be considered more accurate than automatic interview transcription, particularly in cases where there is a lot of background noise, difficult accents, or technical terms. Human transcribers can also take into account nuances of language, context and sarcasm that may be difficult for automatic transcription software to detect.
The general steps in human transcription are as follows:
Preparation: The transcriber listens to or watches the recording to determine the participants, the context and the technical terms used in the conversation.
Transcription: The transcriber listens carefully to the recording and transcribes the words into writing, using a computer or keyboard to enter the text.
Correction: The transcriber reviews the transcript to correct any errors and ensure that the transcript is as accurate as possible.
Formatting: The transcriber can format the transcript using appropriate conventions, such as line breaks, punctuation, capitalization, etc.
Identification: When reviewing the document, the transcriber can ensure that all speakers have been correctly identified.
Delivery: The transcriber sends the finished transcript to the client or end user.
A battle between human and A.I. transcription? There are several reasons why A.I.-based automatic interview transcription may not be as accurate as it should be in terms of interview transcription. Some of the main factors include:
Lack of understanding and precision: Automatic transcription systems may have difficulty transcribing accents, idioms, technical terms and proper names that are not part of their trained vocabulary. These systems can also have problems identifying when someone is quoting someone else, and lacks the comprehension to use appropriate grammar in many cases. This can lead to transcription errors or inconsistencies.
The A.I. is very limited as it’s a program: A.I. systems are still limited in their ability to understand the context of a conversation, which can lead to interview transcription errors or inconsistencies. For example, an A.I. system may have difficulty understanding sarcasm, figures of speech, idioms, homophonies, etc., which may be difficult for automatic transcription software to detect.
A.I. often makes mistakes in transcribing interviews: Automatic transcription systems are trained on data, and if the data is not of good quality or representative of real situations, this can lead to errors in the interview transcription results. For example, if the data used to train an A.I. system comes from a specific geographical region, the A.I. system may have difficulty transcribing accents or idioms from other regions within an interview.
The cost is not really low: Automated interview transcription may be less expensive than human interview transcription, but it may require significant costs to set up and pay for subscription to A.I. systems.
A.I. needs humans: Automatic transcription requires supervision to ensure that errors are detected and corrected, and to ensure that the transcription is as accurate as possible. This may require additional resources for supervision and verification of results. These resources may include staff to oversee the A.I. systems, software to check the results of the automatic transcription and processes to correct errors. There may also be costs associated with training employees to use automatic transcription systems.
Is human transcription more reliable?
We will present four reasons why humans are better at transcribing interviews:
Correction of errors during transcription: Human transcribers can correct errors that occur in automated interview transcription, whereas A.I. systems may be limited in their ability to correct errors. For example, a human transcriber may be able to spot grammatical errors or inconsistencies in the automatic transcription and correct them, whereas an A.I. system may not be able to do so.
Adaptability to specific needs : Human transcribers can adapt to the specific needs of each project or client, whereas A.I. systems are limited by their programming. For example, a human transcriber may be able to transcribe a recording of an interview that contains domain-specific technical terms, whereas an A.I. system may not be able to do so.
Humans are always checking: Human transcribers can review and check the transcript of an interview to ensure its quality, while they’re typing it, whereas A.I. systems may not be able to do this. This may include checking spelling, grammar, punctuation, words and accuracy of the transcription.
Humans can transcribe into different languages: Human transcribers can transcribe different languages, whereas A.I. systems may be limited in their ability to transcribe languages that are not part of their trained vocabulary. For example, a human transcriber may be able to transcribe an interview where there may be people speaking in Spanish, French, German, etc. whereas an A.I. system may not be able to do so.
Conclusion:
In conclusion, human transcription can offer superior accuracy and flexibility compared to A.I.-based automatic transcription. Humans have brains, whereas A.I. is the creation of a human. This means that it cannot surpass it. Now you know exactly why you should choose human interview transcription over automated transcription.
