Enhance Medical Transcription Accuracy with Custom Watson Speech-to-Text Model

Enhance Medical Transcription Accuracy with Custom Watson Speech-to-Text Model

Table of Contents

1. Introduction
2. Customization Feature of Watson speech to text Service
3. Transcribe Panel
4. Base Speech to Text Model
5. Custom Built Model
6. Training the Watson Speech to Text Service
7. Performance Comparison of Base Model and Custom Model
8. Examples of Improved Accuracy by Custom Model
9. Building and Running the App
10. Additional Features of the App
11. Dynamic Training Feature
12. Conclusion

🎯 Introduction

In this article, we will explore a web app that showcases the customization feature of the Watson Speech to Text service. The app is built using JavaScript, React, and Express. We will delve into the various aspects of the app, including the transcribe panel, base speech to text model, custom built model, training the Watson service, performance comparison, and more. So, let's dive in and explore the fascinating world of Speech-to-Text customization!

🚀 Customization Feature of Watson Speech to Text Service

The Watson Speech to Text service provides a powerful customization feature that allows users to train the service to understand new words and phrases. This feature proves especially useful when transcribing audio from specialized domains such as Sports or medicine. By training the service with example audio and text files, users can enhance the accuracy of the transcriptions and cater to specific industry requirements.

🎙 Transcribe Panel

The app's transcribe panel serves as a user-friendly interface for inputting audio files and converting them into text. Users have the option to choose between the base speech to text model or a custom-built model. The base model is designed to transcribe general vocabulary used in day-to-day conversations. On the other HAND, the custom model comes into play when transcribing audio from highly specialized domains.

🧱 Base Speech to Text Model

The base speech to text model provided by the Watson service does an excellent job of transcribing general vocabulary. It accurately converts audio files into text, showcasing its efficiency in everyday conversations. However, when dealing with specific industries or domains, the base model may not be the best choice. That's where the customization feature and the custom built model come into play.

🏗 Custom Built Model

The custom built model is a key highlight of the app. By training the Watson Speech to Text service with example audio and text files, users can create a model tailored to their specific industry requirements. For instance, let's consider the medical industry. By training the service with audio dictation from doctors, the custom model can accurately transcribe medical terms and phrases, surpassing the capabilities of the base model.

🔧 Training the Watson Speech to Text Service

The training process involves using example audio and text files to educate the Watson service on new words and phrases. In this app, we have built a custom model for the medical industry, specifically focusing on dictation from doctors. By following the step-by-step instructions provided in the app's documentation, users can train the Watson service to understand and transcribe industry-specific terms with higher accuracy.

📈 Performance Comparison of Base Model and Custom Model

To showcase the effectiveness of the custom model, let's compare the performance of the base model and the custom model by submitting the same audio file to both. The results highlight the superiority of the custom model in accurately transcribing specialized terms. For example, while the base model returns "lower stardom," the custom model correctly transcribes it as "lower sternum." Such improvements in accuracy make the custom model invaluable in domain-specific Transcription tasks.

✨ Examples of Improved Accuracy by Custom Model

The app provides several examples where the custom model outperforms the base model in transcribing specialized terms. For instance, the custom model correctly transcribes "troponin" as a type of protein, while the base model incorrectly transcribes it as "proponent." Similarly, the custom model accurately transcribes "acute coronary syndrome" and "ulcerative colitis," in contrast to the base model's transcriptions of "a good corn syndrome" and "full sort of colitis," respectively. These examples demonstrate the custom model's capability to capture domain-specific terminology with precision.

🏗 Building and Running the App

The app's documentation provides detailed instructions on how to build and run the application. Users are guided through a step-by-step process, starting from cloning the repository to creating the Watson Speech to Text service and generating the necessary credentials. The documentation covers both using the application and using the command line with Python scripts to achieve the same results. It also emphasizes the importance of upgrading to a standard plan for speech model customization.

🎛 Additional Features of the App

Apart from the transcribe panel and models, the app offers additional features to enhance the user experience and customization capabilities. The Corpora page allows users to submit transcribed text files to train the custom model. On the other hand, the audio page serves a similar purpose but for audio files. These features provide users with the flexibility to fine-tune their custom models with diverse sources of data, further improving the accuracy of the transcriptions.

🔄 Dynamic Training Feature

A standout feature of the app is its dynamic training capability. Users can leverage this feature by making fixes within the transcribed text window. By modifying the text and providing a unique corpus file name, users can retrain their models on the fly. This feature enables continuous improvement of the custom model, allowing users to iteratively refine it and achieve even better transcription results over time.

🎉 Conclusion

In conclusion, the web app showcasing the customization feature of the Watson Speech to Text service opens up a world of possibilities for accurately transcribing specialized domains. The custom built model combined with the training capabilities of the Watson service empowers users to achieve highly accurate transcriptions tailored to their industry-specific needs. With its user-friendly interface and additional features like dynamic training, the app offers a comprehensive solution for anyone seeking reliable speech-to-text customization.

【Highlights】

1. Explore a web app showcasing the customization feature of the Watson Speech to Text service.
2. Delve into the transcribe panel and the options of base and custom models.
3. Train the Watson service using example audio and text files.
4. Compare the performance of the base model and the custom model.
5. Witness examples where the custom model excels in transcribing specialized terms.
6. Follow step-by-step instructions to build and run the app.
7. Leverage additional features like submitting corpora and audio files for training.
8. Experience the dynamic training feature to continually improve the custom model's accuracy.

【Resources】

• IBM Developer - Code Patterns
• GitHub Repo - IBM/Trained-Custom-Speech-Model
• Easi DI - Medical Dictation

FAQ

Q: Can I customize the speech-to-text model for domains other than medicine?
A: Yes, the app allows you to train the Watson Speech to Text service for various domains, including sports, finance, and more. The customization feature enables you to tailor the model to meet the specific requirements of your chosen domain.

Q: How long does it take to train a custom model?
A: The training time depends on the size of your training data and the complexity of the domain. Generally, larger datasets and more specialized domains require additional time for accurate model training.

Q: Does the app support languages other than English?
A: Yes, the app supports multiple languages for speech-to-text transcription. You can train the model with audio and text data in various languages to achieve accurate transcriptions in your desired language.

Q: Can I use the custom model to transcribe live speech?
A: Currently, the app focuses on transcribing pre-recorded audio files. However, with the customizable nature of the Watson Speech to Text service, integrating live speech transcription into the app is possible with additional development and configuration.

Q: How often should I retrain my custom model?
A: The frequency of retraining depends on the evolving nature of your domain and the specific requirements of your application. It's recommended to periodically retrain the model with fresh data to ensure up-to-date and accurate transcriptions.

Q: Is the app compatible with other Watson services?
A: While the app primarily focuses on the customization feature of the Watson Speech to Text service, it can be extended to integrate with other Watson services as per your application needs. The IBM Developer website provides various tutorials and resources to guide you in expanding the app's capabilities.