Mass Luminosity, Inc. (20240220737). PROBABILISTIC MULTI-PARTY AUDIO TRANSLATION simplified abstract

PROBABILISTIC MULTI-PARTY AUDIO TRANSLATION

Organization Name

Mass Luminosity, Inc.

Inventor(s)

Angel Munoz of Dallas TX (US)

Teodor Atroshenko of Valencia (ES)

PROBABILISTIC MULTI-PARTY AUDIO TRANSLATION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240220737 titled 'PROBABILISTIC MULTI-PARTY AUDIO TRANSLATION

• • Simplified Explanation:**

This patent application describes a method for probabilistic multi-party audio translation, which involves processing input text of a communication session to generate translation data and enunciation data, and presenting the enunciation data based on a similarity score.

• • Key Features and Innovation:**
• Utilizes a prediction model and a translation model to process input text.
• Generates translation data and enunciation data.
• Uses a sentence similarity model to calculate a similarity score.
• Presents enunciation data based on the similarity score.

• • Potential Applications:**
• Multilingual communication platforms.
• Language learning tools.
• Conference call translation services.

• • Problems Solved:**
• Facilitates real-time audio translation in multi-party communication.
• Improves accuracy and efficiency of audio translation services.

• • Benefits:**
• Enhances communication between individuals speaking different languages.
• Streamlines the translation process in group conversations.
• Increases accessibility to multilingual content.

• • Commercial Applications:**
• "Probabilistic Multi-Party Audio Translation Method for Enhanced Communication Services"
• Potential use in telecommunication companies, language learning platforms, and international business meetings.

• • Questions about Probabilistic Multi-Party Audio Translation:**

1. How does the method determine the similarity score between translation data and enunciation data? 2. What are the potential challenges in implementing this technology in real-time communication settings?

• • Frequently Updated Research:**

Stay updated on advancements in machine learning models for audio translation and improvements in natural language processing algorithms for multi-party communication.

Original Abstract Submitted

a method implements probabilistic multi-party audio translation. the method includes receiving input text of a communication session. the method further includes processing the input text with a prediction model and a translation model to generate translation data. the method further includes processing the translation data and enunciation data with a sentence similarity model to generate a similarity score. the method further includes presenting the enunciation data based on the similarity score.