Features and Useful Points of Transcription by Format: Audio, Video, Images, PDF

Audio transcription

Audio transcription is the process of listening to recorded audio data and transcribing the content as text. It is used in a variety of fields, including creating minutes, interviews, lectures, video production, legal records, and educational settings, and is an essential process for organizing, sharing, and improving searchability of information. In recent years, advances in AI technology have dramatically improved the accuracy and efficiency of transcription, making it easy for anyone to use.

Audio file formats and characteristics

There are several audio file formats used for transcription, each with its own characteristics. The format you choose will affect sound quality, compatibility, file size, and other factors, so it's important to choose the format that best suits your needs.

MP3

The most common compressed audio format. The file size is small and it can be played on most devices. However, due to the loss of sound quality caused by compression, it may not be suitable for transcriptions where accuracy is important.

WAV

This is an uncompressed, high-quality audio format. Ideal for improving speech recognition accuracy. However, the file size is large, so care must be taken when saving or sharing.

AAC/M4A

This format is often used by Apple products. It has higher sound quality than MP3 and is compatible with iOS. Be careful of compatibility.

FLAC

This lossless compression format reduces file size while maintaining sound quality. It is suitable for high-precision recording, but compatible software may be limited.

How to choose a transcription method

There are three main methods for transcribing audio. Each has its own advantages and disadvantages, so it's important to choose the right method based on your purpose, budget, and time.

① Manual transcription

This method involves a person listening to the audio and typing in the content word for word. It is the most accurate method, and can accurately reflect the speaker's nuances and context. It is particularly useful in situations where accuracy is required, such as legal documents, interviews, and creating meeting minutes. However, it takes time and effort, so it is not suitable for long audio recordings.

② Automatic transcription (voice recognition)

This method uses AI and speech recognition technology to automatically convert speech into text. Representative tools include Google Voice Input, Microsoft Word's voice function, Otter.ai, and AmiVoice, and they are capable of transcribing in real time. While this method offers fast processing speeds and low costs, recognition accuracy can vary depending on the sound quality and speaking style.

③ Hybrid type (automatic + manual correction)

This method creates a base text using automatic transcription, which is then manually corrected and formatted. It offers a good balance of efficiency and accuracy, making it suitable for creating minutes and subtitles. By manually compensating for the weaknesses of automatic transcription, high-quality transcription can be produced in a short amount of time.

To improve the accuracy of voice transcription, it is important to create a recording environment with little noise, utilize speaker identification functions, register technical terms and proper nouns in the tool in advance, and make sure the speaker speaks slowly and clearly.

Key points about audio transcription

When using voice transcription, the quality of the results depends on the app you choose and the settings you use. First, the quality of the audio during recording is crucial. Adjusting the microphone position and ambient noise reduction in the app's settings can significantly improve speech recognition accuracy. When there are multiple speakers, using an app with a display function that identifies who is speaking can improve editing and analysis efficiency. Furthermore, selecting a transcription that displays timecodes makes it easier to understand the timing of speech, making it easier to use in subtitling and video editing. A hybrid approach, in which an automatic recognition tool is used to create a base and then manual corrections are made, is effective in achieving both efficiency and accuracy. By selecting the appropriate app and operation method for your purpose and optimizing the settings, you can accurately capture the content of the audio, enabling use in a wide range of fields, including meeting notes, interview organization, education, and research.

Video transcription

Video transcription is the process of listening to the audio contained in a video and converting the content into text. It is used in a variety of situations, such as YouTube and corporate promotional videos, online lectures, and interview videos, and is an essential process for creating subtitles, organizing information, and improving accessibility. Here, we will introduce the unique features of video transcription and practical points to keep in mind.

Video transcription features

Video transcription requires a higher level of understanding because it incorporates not only audio but also the context of the video. Because video includes facial expressions, actions, and slide content that complement the meaning of spoken words, it is important to consider the overall context of the video rather than simply recognizing the audio. Whether to include text or figures in the video in the transcription also requires careful consideration, depending on the purpose. Another major advantage of video transcription is its ability to incorporate time codes. By matching the timing of speech with video, it can be used as subtitles or captions. Time-coded transcripts are also extremely useful for editing and searching for specific statements. Furthermore, in situations featuring multiple speakers, such as interviews and roundtable discussions, technology is required to identify who is speaking, and environmental sounds such as background music and sound effects can affect the accuracy of speech recognition. Recently, with the increase in videos intended for global distribution, there has been a growing need to combine transcription and translation to create multilingual subtitles. Given these complex factors, video transcription is being used in an increasingly diverse range of situations.

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Image transcription

Image transcription is a technique for extracting text information contained in photos, scanned documents, etc. as text data. This mainly uses a technology called OCR (Optical Character Recognition), and in recent years, advances in AI have greatly improved its accuracy.

Image transcription features

Recommended technologies eliminate the need for manual input from paper documents and screenshots, enabling rapid text conversion and significantly improving work efficiency. This leads to increased automation and data organization, making daily operations smoother. Texted information can be searched for keywords and edited on-screen, increasing information reusability, allowing users to quickly find needed information and flexibly update content. In recent years, an increasing number of tools are available that can handle not only printed documents but also handwritten text and complex layouts, and adjusting settings enables higher recognition accuracy. These technologies are useful in business settings for managing business cards, digitizing invoices, and organizing meeting materials, and in education for digitizing teaching materials and saving blackboard notes. Furthermore, in everyday life, the increasing number of easily operable tools for recording receipts, organizing handwritten notes, and utilizing screenshots on-screen has the potential to dramatically change the way information is managed.

Key points for image transcription

When using OCR technology, it's important to keep several key points in mind. First, image quality has a significant impact on recognition accuracy, making accurate text conversion difficult in images with blurry text or low contrast with the background. For this reason, it's recommended to use images that are as clear and legible as possible. Second, when handling images containing personal information, such as business cards or contracts, careful information management is essential to avoid the risk of information leaks. Furthermore, there are many OCR tools available, both free and paid, each with different recognition accuracy, supported languages, and supported file formats. Comparing and considering these factors based on your purpose and usage environment and selecting the optimal tool will lead to efficient and safe use.

PDF transcription

PDF transcription is the process of extracting the text information contained in a PDF file and converting it into editable text data. Scanned PDFs, in particular, do not support the usual copy and paste functionality, so OCR technology is required to read the text.

Features of PDF transcription

When transcribing PDFs, it's important to understand the difference between standard text-based PDFs and image-based PDFs. While text can be extracted directly from text-based PDFs, text information cannot be extracted from PDFs saved as images without the use of OCR technology. There are a variety of OCR tools that can handle image-based PDFs, including Adobe Acrobat Pro, Google Docs, Smallpdf, and PDF Candy, both free and paid. Because each tool offers different features and accuracy, it's effective to use the appropriate tool for your purpose. Furthermore, OCR technology has significantly improved in recent years thanks to advances in AI, with more tools now able to handle handwritten text and complex layouts. As a result, digitizing previously difficult documents can now be done more accurately and efficiently, making PDF transcription increasingly important in work, learning, and everyday life.

Key points for PDF transcription

When transcribing PDFs, keeping several important points in mind will ensure a more accurate and safe process. First, image quality has a significant impact on recognition accuracy, so blurry images and low-resolution PDFs are more likely to result in misrecognition. Therefore, it is recommended to use files with as clear and high quality as possible. Second, layout complexity is also a factor that affects character extraction. Especially with tables and columns, the order of characters can be distorted, so it is important to check the content after extraction and make any necessary corrections. Also, sufficient consideration must be given to security and personal information management. When using cloud-based OCR tools, be careful about the content of the files you upload. If the file contains highly confidential information, it is preferable to process it locally if possible. By keeping these points in mind, you can improve the accuracy and security of your PDF transcription and use it with peace of mind.

As such, transcription technology, which supports a variety of formats such as audio, video, images, and PDFs, has made a significant contribution to improving information organization, sharing, and searchability, becoming indispensable in business, education, and everyday life. Each format has its own unique characteristics and considerations, and choosing the appropriate method and tool depending on the purpose and environment is the key to improving accuracy and efficiency. With the evolution of AI technology, transcription has become increasingly familiar and flexible, and it will continue to be used in many situations as a powerful tool to expand the possibilities of information utilization.