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 - Language learning tools
Problems Solved: - Minimizing delay in speech-to-speech conversion - Maintaining high quality in real-time audio output
Benefits: - Enhanced user experience with minimal delay - Improved accuracy in speech conversion - Efficient real-time communication support
Commercial Applications: Title: Real-time Speech Translation Services This technology can be utilized in: - Virtual meetings and conferences - Language interpretation services - Educational platforms for language learning
Questions about Streaming Speech-to-Speech Conversion: 1. How does the streaming-based approach improve real-time speech conversion? 2. What are the key advantages of using a hybrid model in speech-to-speech conversion?
Frequently Updated Research: Stay updated on advancements in real-time speech-to-speech conversion technology to ensure optimal performance and accuracy.
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.
