Audio Processing Apparatus Noise Cancellation Using Reference Signals
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Solution Overview
Problem
Virtual assistants face difficulties in differentiating human speech from interfering noise in environments with multiple audio sources, leading to poor speech recognition performance.
Innovation Solution
An audio processing apparatus that receives audio signals from microphones and interconnected devices, using reference signals to remove noise components, prioritizing noise removal based on energy levels and correlation, and employing neural networks for effective noise cancellation and speech recognition.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If noise cancellation techniques are applied to improve speech recognition in noisy environments, then speech recognition accuracy is improved, but device complexity increases
Solution Approach 1:
The system segments the audio signal processing by separating noise removal from speech recognition. The audio processing apparatus first removes identified noise components from the audio signal, then the speech recognition system processes the cleaned signal. This segmentation allows each component to specialize, improving overall accuracy while managing complexity through modular design.
Solution Approach 2:
The system performs preliminary noise removal before speech recognition. By identifying and removing noise components from the audio signal in advance, the speech recognition system receives pre-processed input with reduced interference, thereby improving recognition accuracy without requiring the recognition system itself to handle complex noise cancellation.
2Measurement precision
If multiple noise components are removed simultaneously to improve speech isolation, then speech recognition accuracy is improved, but processing time increases
Solution Approach 1:
The system applies different processing priorities to different noise components based on their local characteristics. Noise components are prioritized for removal based on their energy levels and correlation with the audio signal, allowing the system to focus computational resources on the most problematic noises first, thereby improving speech isolation efficiency.
Data Source
AI summary
An audio processing apparatus, comprising: a first receiver configured to receive one or more audio signals derived from one or more microphones, the one or more audio signals comprising a speech component received from a user and a first noise component transmitted by a first device; a second receiver configured to receive over a network and from the first device, first audio data corresponding to the first noise component; one or more processors configured to: remove the first noise component from the one or more audio signals using the first audio data to generate a first processed audio signal; and perform speech recognition on the first processed audio signal to generate a first speech result.