Google llc (20240265215). STABLE REAL-TIME TRANSLATIONS OF AUDIO STREAMS simplified abstract
Contents
STABLE REAL-TIME TRANSLATIONS OF AUDIO STREAMS
Organization Name
Inventor(s)
Dirk Ryan Padfield of Seattle WA (US)
STABLE REAL-TIME TRANSLATIONS OF AUDIO STREAMS - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240265215 titled 'STABLE REAL-TIME TRANSLATIONS OF AUDIO STREAMS
Simplified Explanation: The patent application describes methods, systems, and apparatus for generating stable real-time textual translations in a target language from an input audio data stream recorded in a source language.
- **Obtaining an audio stream in a first language**
- **Generating partial transcriptions at successive time intervals**
- **Translating each partial transcription into a second language**
- **Using a model to identify stable portions of the translated text**
- **Displaying the stable portions on a user device**
Key Features and Innovation:
- Real-time translation of audio data streams
- Partial transcription generation for efficient translation
- Stability prediction for accurate translation output
- User-friendly display of translated text
Potential Applications:
- Language interpretation services
- Live event translation
- Educational tools for language learning
- Communication aids for multilingual environments
Problems Solved:
- Overcoming language barriers in real-time communication
- Enhancing accessibility for non-native speakers
- Improving efficiency in translation processes
Benefits:
- Facilitates seamless cross-language communication
- Increases accessibility to information for diverse audiences
- Enhances user experience with accurate and stable translations
Commercial Applications: Title: Real-Time Audio Translation Technology for Multilingual Communication This technology can be applied in industries such as:
- Telecommunications
- Language interpretation services
- Education and training
- International business and diplomacy
Prior Art: Researchers can explore prior art related to real-time audio translation systems, machine learning models for language processing, and audio transcription technologies.
Frequently Updated Research: Stay updated on advancements in machine learning algorithms for natural language processing, real-time translation technologies, and user interface design for language applications.
Questions about Real-Time Audio Translation Technology: 1. How does this technology compare to existing real-time translation systems? 2. What are the potential challenges in implementing this technology on a large scale?
2. Another relevant generic question, with a detailed answer: How does the stability prediction model improve the accuracy of translated text in real-time applications? The stability prediction model analyzes translated text to identify and display stable portions, ensuring more reliable and coherent translations for users.
Original Abstract Submitted
methods, systems, and apparatus, including computer programs encoded on a computer storage medium, that facilitate generating stable real-time textual translations in a target language of an input audio data stream that is recorded in a source language. an audio stream that is recorded in a first language is obtained. a partial transcription of the audio can be generated at each time interval in a plurality of successive time intervals. each partial transcription can be translated into a second language that is different from the first language. each translated partial transcription can be input to a model that determines whether a portion of an input translated partial transcription is stable. based on the input translated partial transcription, the model identifies a portion of the translated partial transcription that is predicted to be stable. this stable portion of the translated partial transcription is provided for display on a user device.
