How does ASR Transcription Work?

ASR transcription technology has revolutionized how we convert speech into text, taking away the need for manual input. While this technology is not new, technological advancements, especially in Artificial Intelligence (AI), have paved the way for more advanced ASR transcription systems.

But what is ASR transcription, how exactly do these systems work, and how can you put them into use to enhance your communication?

This article delves deeper into this topic by:

What is Automatic Speech Recognition?

Automatic Speech Recognition (ASR) is the technology that converts spoken words into written text. It involves a complex blend of artificial intelligence, machine learning, and linguistics. At its core, ASR transcription is designed to mimic the human ability to listen and transcribe spoken words accurately and efficiently.

ASR has many applications, such as voice assistants, voice search, voice typing, captioning, and transcription. It is applied in various domains and scenarios that require speech to be converted into text. Some of the common applications are:

Live captioning and transcription

ASR technology can provide real-time or near real-time subtitles or transcripts for audio or video content, such as streaming movies, podcasts, meetings, lectures, or interviews.

This can improve the accessibility, comprehension, and retention of the content for the viewers or listeners.

Virtual assistants and chatbots

ASR technology can enable natural and conversational interactions between humans and machines, such as voice assistants, voice search, voice typing, or voice control.

This can enhance the functionality and usability of the machines and create new possibilities for human-machine collaboration.

Speech analytics

ASR technology can analyze speech data to extract insights and information, such as sentiment, emotion, intent, or speaker identification. This can help businesses improve customer service, marketing, sales, or product development.

Transcription services

ASR technology has significantly enhanced transcription services. It’s used extensively in fields such as legal and journalism. There is also ASR medical transcription, making it easier and quicker to convert audio recordings into written documents.

Voice assistants

Virtual assistants like Siri, Alexa, and Google Assistant employ ASR to comprehend and respond to voice commands and queries, enabling natural and intuitive interactions.

Customer service

Many companies employ ASR in their Interactive Voice Response (IVR) systems, streamlining automated customer service interactions and reducing human intervention.

These are just some of the examples of where ASR technology is applied. There are many more potential applications that can benefit from ASR technology in the future.

How Does Automatic Speech Recognition Work?

In layman’s terms, Automatic Speech Recognition (ASR) works by converting spoken words into written text. However, it follows an intricate process for it to work. Here is a brief overview of how these systems work:

1. Audio preprocessing

The input audio is converted into a digital signal and processed to remove noise, enhance quality, and normalize volume. This step helps to improve the clarity and consistency of the speech signal for the next steps.

2. Feature extraction

The processed audio signal is transformed into a sequence of features that represent the acoustic characteristics of the speech, such as pitch, energy, and spectral shape.

These features are usually represented by vectors of numbers. This step helps to reduce the dimensionality and complexity of the speech signal for the next steps.

3. Speech recognition

The sequence of features is fed into a speech recognition model, a machine learning algorithm that learns to map the features to the corresponding words or phonemes (the smallest units of sound in a language).

The speech recognition model outputs a sequence of words or phonemes with probabilities or scores that indicate how confident the model is about each prediction. This step helps to generate the most likely transcription of the speech signal for the next step.

4. Language modeling

The sequence of words or phonemes is refined by a language model, another machine-learning algorithm that learns to predict the next word or phoneme based on the previous ones.

The language model assigns probabilities or scores to different word or phoneme sequences and selects the most likely one as the final output. This step helps to improve the fluency and accuracy of the transcription by considering the context and structure of the language.

Automatic Speech Recognition Technology With Krisp

ASR technologies are a game-changer in the industry. However, it is important to note that not all ASR solutions are created equal.

Some may have low accuracy, high latency, limited functionality, or high cost. That’s why you need Krisp, an advanced AI transcription service that employs ASR technologies combined with the latest machine learning, speech-to-text, and AI software.

Krisp’s AI meeting assistant makes it easy to get highly accurate verbatim transcriptions of your remote or hybrid virtual meetings , regardless of the platform you use. Whether you use Zoom, Teams, Google Meet, or any other video conferencing tool, Krisp can seamlessly integrate with it and provide you with real-time or post-meeting transcriptions.

You can also use Krisp to record and transcribe audio or video files from your device or cloud storage.

Using Krisp to get accurate transcriptions is easy:

  1. Create an account and download the Krisp app to your laptop or computer. It’s compatible with Windows, Mac, and Linux.
  2. Open your online meeting platform app , e.g., Zoom or Teams.
  3. On the meeting app, change the settings to allow Krisp to be the microphone and speaker provider.
  4. Join or start your meetings as usual, and Krisp automatically works in the background to get you transcriptions.
  5. Once the meeting is done, you can access the transcription immediately at the Krisp dashboard, where you can share, make edits, or invite collaborators.

Krisp AI has many features and benefits that make it stand out from other ASR solutions:

High accuracy

Krisp uses state-of-the-art ASR models that can recognize speech with over 95% accuracy. Krisp also uses natural language processing (NLP) techniques to correct grammar, punctuation, and spelling errors in the transcripts.

Low latency

Krisp can transcribe speech in real-time or near real-time, depending on your internet speed and device performance. You don’t have to wait long to get your transcripts after the meeting ends.

Noise cancellation

Krisp can filter out background noise from both sides of the conversation using its patented noise suppression technology. This can improve the quality and clarity of the audio and the transcripts.

Automated note-taking

Krisp’s AI note-taker makes extracting important notes from the transcription easy, highlighting meeting takeaways , key discussions, decisions, and action items. This can help you save time and effort in creating and sharing meeting notes.

Meeting minutes app

Krisp also offers a state-of-the-art meeting minutes app . By using this tool, you can quickly generate meeting minutes that can be used for official purposes and record-keeping, saving you time and resources. This feature uses the meeting transcription, so there is minimal output required from your end.

Speaker identification

Krisp can identify and label different speakers in the transcripts using its speaker identification technology. This can help you keep track of who said what in the meeting.

Keyword extraction

Krisp can extract and highlight important keywords and phrases from the transcripts using its keyword extraction technology. This can help you summarize and review the main points of the meeting.

Easy to use

Unlike many other ASR systems, Krisp is pretty straightforward to use without the need for additional setup complexities, plugins, and extensions. Moreover, you don’t need to record the meeting to get its transcription. With Krisp, you can easily get a Teams meeting transcription without recording or when using any other platform.

Customization

Krisp allows you to customize your transcription preferences, such as language, accent, format, style, and vocabulary. You can also add custom words or phrases to your personal dictionary to improve the recognition of domain-specific terms.

Security

Krisp ensures the privacy and security of your data by using end-to-end encryption and complying with GDPR and CCPA regulations. Your data is not stored or shared with anyone without your permission.

Conclusion

Automatic Speech Recognition has many applications that we can use in everyday life — from meeting transcriptions to customer service.

Krisp stands out as one of the best ASR systems offering more than just accurate AI transcriptions, focusing on quality meeting notes and summaries, as well as the meeting minutes app, which can save you significant time and resources.

Try Krisp today and see how it can transform your communication and collaboration.

Frequently Asked Questions

Is ASR Transcription as accurate as human transcriptionists?

ASR transcription has made significant strides in accuracy, but it may not always match the precision of human transcriptionists. The accuracy of ASR depends on various factors, including the quality of the audio, background noise, accents, and the specific ASR system used.

Can ASR Transcription be integrated with other tools or software?

Yes, ASR transcription can often be integrated with other tools and software systems. Many ASR providers, like Krisp, offer APIs that allow seamless integration with various applications, including transcription services, voice assistants, customer service solutions, and more. This integration enhances automation and efficiency in numerous industries.

In what industries or applications is ASR Transcription commonly used?

ASR transcription finds applications across a wide range of industries, including but not limited to legal, medical, academic, and journalism industries.

Can ASR Transcription be customized for specific industries or jargon?

Yes, you can customize ASR transcription for specific industries, accents, and specialized jargon. This involves training the ASR system with domain-specific data and vocabulary to improve accuracy in those contexts.

How can I optimize the accuracy of ASR Transcription for my recordings?

To optimize the accuracy of ASR Transcription for your recordings, consider the audio quality with minimal background noise, clear pronunciation of words, and label or identify the different speakers to improve speaker-specific accuracy. Moreover, ensure to review and correct ASR-generated transcripts to ensure accuracy for critical content.