A Bluetooth-based wireless headphone audio transmission method

By integrating a sensor array and an improved CNN convolutional neural network into Bluetooth headsets to eliminate noise, and combining the BERT-ResNet model to identify scenes and switch codecs, the problem of poor noise reduction and dynamic bandwidth adjustment in traditional Bluetooth headset audio transmission is solved, thereby improving audio quality and transmission success rate.

CN120602913BActive Publication Date: 2026-01-30SHENZHEN LANQI CHUANGFA TECH CO LTD
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Patent Information

Application Number
CN202510709036.5
Authority / Receiving Office
CN · China
Patent Type
Patents(China)
Current Assignee / Owner
Filing Date
2025-05-29
Publication Date
2026-01-30
Estimated Expiration
2045-05-29

AI Technical Summary

Technical Problem

Traditional Bluetooth headset audio transmission methods cannot adjust noise reduction strategies in real time according to complex and changing environments and user movement states, resulting in poor noise reduction effects; when Bluetooth channel bandwidth changes dynamically, the codec cannot be adjusted in time, causing audio stuttering and distortion; existing audio data transmission does not distinguish priorities, and cannot guarantee the reliable transmission of critical information under bandwidth-limited conditions.

Method used

The system acquires user motion status and environmental noise through a sensor array in the wireless earphone, eliminates noise using an improved CNN convolutional neural network and adaptive filtering algorithm, identifies the scene and predicts available bandwidth using a BERT-ResNet fusion model, dynamically switches codecs, and transmits audio data in segments through the Bluetooth main channel and auxiliary channel.

Benefits of technology

It enables accurate extraction of noise spectrum features in complex environments, eliminates motion friction noise, improves audio purity and smoothness, increases audio transmission success rate, reduces stuttering and distortion, and meets users' personalized needs.

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Abstract

This invention discloses a Bluetooth-based wireless earphone audio transmission method. It acquires environmental audio matrix data through a sensor array in the wireless earphone; extracts noise spectrum features from the environmental audio matrix data using an improved CNN convolutional neural network; and eliminates motion friction noise in the matrix data using an adaptive filtering algorithm to obtain dual-channel noise-reduced data. The dual-channel noise-reduced data is input into a fusion model to identify the user's current scene. Combining Bluetooth RSS I signals and historical channel data, it predicts the available bandwidth within the next 5ms. Based on the scene identification result and available bandwidth, it switches the codec. Based on the codec, it segments the audio data stream into high-priority and low-priority data packets, which are transmitted through the Bluetooth main channel and auxiliary channel, respectively. This improves the audio data transmission success rate, effectively reduces audio stuttering and distortion, and enhances the user's listening experience and satisfaction.
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