Noise reduction solution for TWS Bluetooth headset based on bone vibration sensor

For more and more users who are running around in subways, buses, and airports, noise reduction is a very important point in the use of headphones. In order to solve this problem, TWS Bluetooth headsets were born. Today I will talk about a noise reduction solution for TWS Bluetooth headset based on bone vibration sensor.

First of all, let's understand what is a TWS Bluetooth headset. TWS is the abbreviation of True Wireless Stereo, that is, true wireless stereo. Technically, it means that the mobile phone is connected to the main earphone, and then the main earphone is connected to the slave earphone wirelessly through Bluetooth, so as to realize the true wireless separation of the left and right channels of Bluetooth.

Bone vibration sensor detection principle

When a person speaks, the vibration signal generated by the vocal cords propagates in two ways: one is to propagate outward through the air medium, and the other way is to propagate outward through the bones and muscles of the human brain, causing the vibration of the auricle. . The bone vibration sensor uses the latter transmission method to detect the vibration signal of the auricle and pick up the wearer's voice information. The bone vibration sensor is not sensitive to the sound wave signal propagating in the air, and has a natural inhibitory effect on the sound signal propagating in the air. Therefore, the call noise reduction algorithm is simpler and more natural, the noise suppression is more effective, and it can provide a better uplink. call effect.

Comparison of noise reduction methods for TWS headphones

There are many types of TWS headphones on the market. For ENC (Environmental Noise Cancellation) noise reduction, there are various product forms such as single microphone, dual microphone, triple microphone and bone vibration sensor according to different price and performance positioning.

The single microphone solution has an advantage in price, the main control chip requires a lower threshold, and the structure is not limited. The neural network algorithm is used to identify and filter out noise signals. However, the noise reduction effect of the single-microphone solution is general, and the noise recognition and suppression of complex scenes is not very obvious. Dual microphones can be adapted to a variety of forms, have a better experience in most high-noise scenarios, and are cost-effective, and are currently the mainstream solution for ENC noise reduction.

Dual microphone ENC noise reduction, using two microphones with a certain distance, so that the sound signals in different directions can be recognized. The minimum distance between the two microphones is generally 10mm. The algorithm uses a relatively mature beam forming algorithm, the waveform points to the sound source of the wearer's speech, enhances the signal sensitivity in the direction of the sound source, and suppresses the signal sensitivity in other directions, thereby eliminating noise.

Sanmai ENC noise reduction generally reuses the Feedback Microphone (FB) of Active Noise Cancellation (ANC). The FB microphone is used to detect the sound signal transmitted by the vocal cords to the earphone through the cochlea. Most of the noise-cancelling headphones are in-ear wearing. The rubber sleeve of the headphones has a good sealing effect, which can isolate the external environment noise. Sanmai ENC noise reduction, suitable for most scenarios, has good wind noise resistance, but the algorithm is complex and the price is relatively high.

The combination of microphone and bone vibration has better anti-interference performance of environmental human voice, and the distortion of the caller's voice is small. Wind noise is a pain point for most earphones. When the wind speed is greater than 5m/s, the microphone will be saturated and distorted. At this time, the microphone loses the ability to capture voice signals, and the bone vibration sensor does not respond to air fluctuations, so even in high wind speed conditions The voice signal can still be accurately captured. In addition, for bean-type headphones, due to the compact space and small size, it is difficult for the two microphones to be separated, so the noise reduction effect of the dual-mic ENC is not good in this case. A call microphone and a bone vibration sensor can achieve a better call effect, strong wind noise resistance, and good noise suppression effect. The algorithm does not require complex beamforming, and a simple voice algorithm can be implemented. The overall solution Cost-effective, used by more and more headphone manufacturers.

Bone Vibration Sensor Design

Based on Micro-Electronic-Mechanical-System (MEMS) processing technology, a micron-sized elastic beam structure and a mass of a certain weight are processed on a silicon substrate to form a vibration-sensitive mechanical structure. The capacitor plate on the mass block and the capacitor plate on the substrate form a comb-shaped movable capacitor. When vibration is applied to the device, the mass block vibrates, which drives the capacitor comb teeth to vibrate. change, so the capacitance changes.

The application specific integrated circuit (ASIC) inside the bone vibration sensor extracts, converts and amplifies the weak capacitive signal, and outputs the vibration signal in the form of voltage, which is similar to the output signal of the traditional MEMS microphone, which is convenient for the Bluetooth master to carry out signal processing.

The above is the noise reduction solution for TWS Bluetooth headset based on bone vibration sensor, I hope it can help everyone.