Google llc (20240135117). METHOD FOR SPEECH-TO-SPEECH CONVERSION simplified abstract
Contents
- 1 METHOD FOR SPEECH-TO-SPEECH CONVERSION
- 1.1 Organization Name
- 1.2 Inventor(s)
- 1.3 METHOD FOR SPEECH-TO-SPEECH CONVERSION - A simplified explanation of the abstract
- 1.4 Simplified Explanation
- 1.5 Potential Applications
- 1.6 Problems Solved
- 1.7 Benefits
- 1.8 Potential Commercial Applications
- 1.9 Possible Prior Art
- 1.10 How does this technology handle different accents and speech patterns?
- 1.11 What is the computational resource requirement for running this model in real-time?
- 1.12 Original Abstract Submitted
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 20240135117 titled 'METHOD FOR SPEECH-TO-SPEECH CONVERSION
Simplified Explanation
The present disclosure describes a streaming speech-to-speech conversion model that includes an encoder running in real-time while a user is speaking, followed by a decoder generating 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 by using a hybrid model approach that combines look-ahead in the encoder and a non-causal stacker with 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 the encoder and non-causal stacker with non-causal self-attention
Potential Applications
This technology could be applied in real-time translation services, virtual assistants, language learning tools, and communication devices for individuals with speech impairments.
Problems Solved
1. Minimizes delay in speech-to-speech conversion 2. Maintains high conversion quality in real-time scenarios
Benefits
1. Improved user experience with real-time speech conversion 2. Enhanced accessibility for individuals with speech impairments 3. Efficient communication in multilingual settings
Potential Commercial Applications
"Real-Time Speech-to-Speech Conversion Technology for Virtual Assistants and Language Learning Tools"
Possible Prior Art
Prior art in speech recognition and translation technologies may exist, but specific examples are not provided in this disclosure.
Unanswered Questions
How does this technology handle different accents and speech patterns?
The abstract does not mention how the streaming speech-to-speech conversion model adapts to various accents and speech patterns.
What is the computational resource requirement for running this model in real-time?
The disclosure does not provide information on the computational resources needed to implement the streaming speech-to-speech conversion model in real-time.
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.
