How does Anthiago AI Works?


Anthiago AI is an automatic transcription service that can convert audio and video files into text quickly and accurately. It uses advanced speech recognition technology to listen to audio, decipher the words, and transcribe them into text.Transcribing audio and video content is a tedious and time-consuming process. However, with advancements in artificial intelligence and machine learning, automated transcription tools like Anthiago AI are revolutionizing this workflow.

In this article, we’ll explore how Anthiago AI works under the hood. We’ll cover:

  • Overview of automatic transcription and its benefits
  • How Anthiago AI transcribes audio/video into text
  • The transcription technology and machine learning models used
  • Accuracy levels and supported languages
  • Primary use cases and applications
  • Pros and cons of using Anthiago AI

Understanding the transcription process and technology that powers Anthiago AI can help you determine if it’s the right automated tool for your transcription needs. Let’s get started.

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The Benefits of Automated Transcription

Before diving into how Anthiago AI works, let’s first discuss why automated transcription is useful.

Manual transcription is tedious and time-consuming. For a one hour long video, it can take 6-10 hours for a human transcriber to transcribe it accurately. The costs also add up, with professional transcriptions costing $1-$3 per minute of audio.

Automated transcription tools like Anthiago AI can transcribe videos and audio files much faster. The transcription happens almost instantly rather than taking hours.

Some key benefits include:

  • Speed: Automated tools are significantly faster than manual transcription. Transcriptions can be generated in a few minutes rather than hours.
  • Cost: Automated services like Anthiago AI offer free transcription up to a certain limit. There are also affordable paid plans.
  • Efficiency: You don’t have to spend time and effort on manual transcriptions. The process is automated.
  • Scalability: You can transcribe hundreds of files without issues. For large volumes, automated services are more scalable.
  • Accessibility: Automated transcripts make video and audio content more accessible for people with disabilities.

For these reasons, automated transcription tools are becoming popular for transcription needs small and large.

How Does Anthiago AI Transcribe Audio & Video into Text?

Now that we’ve covered the benefits, let’s understand how Anthiago AI is able to take an audio or video file as input and automatically generate a text transcript as output.

The transcription process involves several steps:

1. Input File Processing

Anthiago AI first takes the audio or video file that needs to be transcribed and processes it to extract the audio. For video files, it strips out the audio track from the video file.

The audio is then optimized – background noises are removed, audio levels are normalized, and the file is prepared for feeding into the transcription engine.

2. Feeding Audio to Transcription Engine

The optimized audio file is then fed into Anthiago AI’s advanced speech-to-text transcription algorithms.

These algorithms analyze small chunks of the audio sequentially, listening to the speech and deciphering the words spoken by the speaker(s).

3. Speech Recognition Model

The core of Anthiago AI’s transcription capabilities lies in its deep neural network speech recognition models. These models have been trained on thousands of hours of speech data.

The models can accurately detect speech, isolate words, and convert the spoken audio into text transcripts. The models can understand context and grammar to transcribe audio accurately.

Anthiago AI uses deep learning algorithms like long short-term memory (LSTM) neural networks that can process speech sequentially and have contextual understanding.

4. Generating Transcripts

As the audio file is processed chunk-by-chunk, the speech recognition models keep transcribing it into text in real-time.

The transcripts are time-stamped, so you can see exactly when each phrase in the audio file was said. The final output is a complete, formatted transcript of the entire audio/video file.

5. Post-Processing Transcripts

After the initial transcription, Anthiago AI cleans up the transcript file – correcting spelling errors, formatting the text properly with paragraphs and speaker identifications.

The transcript is the optimized to make it easy to read and edit if required.

This multi-step process is how Anthiago AI is able to automate transcription for audio and video files with great speed and reasonable accuracy.

Accuracy Levels of Anthiago AI

An important consideration for any automated transcription service is accuracy. How accurately can it transcribe the audio into text?

Anthiago AI has an average accuracy of 90% based on internal tests. But accuracy can vary based on:

  • Audio/video quality: Higher quality audio with clear speech results in better accuracy. Audio with background noise or poor quality leads to more transcription errors.
  • Speaker clarity: Clear speech where words are enunciated properly will transcribe more accurately. Mumbled or rapid speech makes it harder for the AI to decipher words.
  • Language: Anthiago AI’s speech recognition models are more accurate for widely spoken languages like English, Spanish, French rather than less common languages.
  • Vocabulary: Technical jargon or niche vocabulary can be challenging for AI models leading to more errors.

While Anthiago AI does fairly well with accuracy, expect some errors for complex audio with multiple speakers. The transcripts generated may require a human editor for 100% accuracy.

Languages Supported by Anthiago AI

Anthiago AI supports transcription of audio/video files in multiple popular languages:

  • English
  • Spanish
  • French
  • German
  • Italian
  • Dutch
  • Portuguese
  • Russian
  • Polish

It can auto-detect the language in the media file and will transcribe accordingly.

The accuracy levels vary slightly based on the language, but remain in the 80-95% range for most supported languages. This wide language support makes Anthiago useful for transcription needs across geographies.

Primary Use Cases of Anthiago AI

Now that we understand how it works and its capabilities, what are some of its primary applications and use cases?

1. Transcribing Videos

One of the most popular uses of Anthiago AI is to automatically transcribe video content from platforms like YouTube or Vimeo.

Simply provide the video URL, and Anthiago AI will transcribe the video typically within a few minutes.

The transcripts can help you search and analyze video content better. You can also use the transcripts to provide subtitles and improve accessibility.

2. Podcast Transcription

Podcasters can use Anthiago AI to get automated transcripts of their podcast episodes. The text transcripts make the podcast content more discoverable through SEO.

Transcripts are also useful for podcast editors and repurposing podcast audio into blog posts or other formats.

3. Media/News Transcription

Media production teams often have large archives of audio and video content. Anthiago AI can be used to batch transcribe these media assets for easier searching and analysis.

News media firms can also use it to transcribe interviews and field reports faster.

4. Business Meetings & Presentations

Transcripts of meetings, corporate presentations, training sessions, and webinars can be useful for people who missed the live event or want to recall discussions.

Anthiago AI provides fast automated meeting transcripts without needing human transcribers.

5. Academic Lectures & Research

In academic settings, Anthiago AI can transcribe lectures, seminars, conference talks automatically. Researchers can transcribe interviews and field recordings.

The transcripts support research and make information more accessible to students.

6. Customer Support Teams

Customer support teams can use Anthiago AI to transcribe call recordings with customers to analyze interactions and find common issues.

For dispute resolution, call transcripts provide useful records of conversations.

The Pros and Cons of Using

Let’s now summarize some key advantages and limitations of using Anthiago AI for automated transcription:


  • Speedy transcription for audio & video
  • Free transcription for 60 minutes of audio per month
  • Reasonable accuracy with constant improvements
  • Multi-language support
  • Useful for a variety of use cases and industries


  • Not 100% accurate, occasional transcription errors
  • Formatting issues may require clean up
  • Cannot transcribe multiple speakers automatically
  • Privacy concerns around sending media files to third-party service

Overall, this is one of the better automated transcription tools available today considering its fast performance, language support, and continual improvements in accuracy.

It excels at creating rough draft transcripts that still require some human editing but drastically reduce the overall time investment. For many business and academic use cases, it hits the sweet spot between affordability, speed and accuracy.


Transcription is a necessary but tiresome process for converting valuable audio content into text. Automated solutions like Anthiago AI make this easier through advanced speech recognition capabilities.

As we learned, Anthiago AI uses deep neural networks models trained on vast speech data to listen to audio files and transcribe them with decent accuracy. The multi-step process results in formatted text transcripts of the spoken audio/video content.

While occasional errors are inevitable, Anthiago AI hits the right balance for many use cases with fast, affordable transcription of media files in various languages. With constant improvements in its transcription engine, the accuracy and capabilities of this AI tool will only get better.

Key Takeaways:
  • Automated transcription tools like Anthiago AI deliver speed, cost and efficiency advantages over manual transcription.
  • Its uses advanced deep learning speech recognition models to listen and transcribe audio into time-stamped text transcripts.
  • It has average accuracy of 90% but can vary based audio quality, speaker clarity and language.
  • Its supports transcription in 9 major languages and is useful for transcribing videos, podcasts, meetings, lectures and more.
  • For most use cases, it provides a fast, affordable way to create draft transcripts that may require some human editing.

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