GOOGLE LLC (20240232546). METHOD FOR SPEECH-TO-SPEECH CONVERSION simplified abstract
Contents
METHOD FOR SPEECH-TO-SPEECH CONVERSION
Organization Name
Inventor(s)
Oleg Rybakov of Redmond WA (US)
Fadi Biadsy of Sandyston NJ (US)
METHOD FOR SPEECH-TO-SPEECH CONVERSION - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240232546 titled 'METHOD FOR SPEECH-TO-SPEECH CONVERSION
The present disclosure pertains to a streaming speech-to-speech conversion model, where an encoder operates in real-time while a user is speaking, and a decoder generates output audio in real-time after the speaking stops. This streaming-based approach minimizes delay and maintains conversion quality compared to non-streaming server-based models. A hybrid model combines look-ahead in the encoder with a non-causal stacker and non-causal self-attention.
- Encoder runs in real-time while user is speaking
- Decoder generates output audio in real-time after speaking stops
- Streaming-based approach reduces delay and maintains conversion quality
- Hybrid model combines look-ahead in encoder with non-causal stacker and self-attention
Potential Applications: - Real-time translation services - Live captioning for events - Assistive technology for individuals with speech impairments
Problems Solved: - Minimizing delay in speech-to-speech conversion - Maintaining high quality in real-time audio output
Benefits: - Improved user experience with minimal delay - Enhanced accessibility for speech-impaired individuals - Efficient real-time translation services
Commercial Applications: Title: Real-time Speech-to-Speech Translation Technology for Live Events This technology can be utilized in live events, conferences, and meetings to provide real-time translation services, enhancing communication for multilingual audiences. It can also be integrated into assistive devices for individuals with speech impairments, expanding its market reach and impact.
Questions about Speech-to-Speech Conversion Technology:
1. How does the streaming-based approach improve real-time speech-to-speech conversion? The streaming-based approach reduces delay and maintains conversion quality compared to non-streaming server-based models, enhancing the overall user experience.
2. What are the potential applications of this hybrid model in the field of speech-to-speech conversion? The hybrid model combines look-ahead in the encoder with a non-causal stacker and self-attention, making it suitable for real-time translation services, live captioning, and assistive technology for speech-impaired individuals.
Original Abstract Submitted
the present disclosure relates to a streaming speech-to-speech conversion model, where an encoder runs in real time while a user is speaking, then after the speaking stops, a decoder generates output audio in real time. a streaming-based approach produces an acceptable delay with minimal loss in conversion quality when compared to other non-streaming server-based models. a hybrid model approach for combines look-ahead in the encoder and a non-causal stacker with non-causal self-attention.
