Guideline- WTM2101 Hearing Aids Solution

 Hearing aids and cochlear implants are the current solutions for individuals with severe hearing loss. In addition to the requirements of miniaturization and reduced power consumption, with the advent of the artificial intelligence era, intelligence is becoming a new trend in the development of hearing aids.

Witmem(Zhicun) Technology has introduced a chip hearing aid solution, the WTM2101 chip, which incorporates a storage-computing integrated architecture, breaking the limitations of storage walls and possessing the advantages of high computing power and low power consumption. This chip can facilitate product launches and drive the transition into a new era of intelligent hearing aids.

The WTM2101 chip, with its storage-computing integrated architecture, boasts an AI computing power of up to 50 Gops operations per second (Gops). Compared to existing wearable device chips, it offers tens to hundreds of times improvement in AI computing power. ZhiCun Technology's storage-computing integrated module is based on high-density non-volatile memory, supporting up to 1.8 million 8-bit quantized deep learning algorithm parameters and the simultaneous execution of 2-3 high-performance models.

 

The main functions of the WTM2101 hearing aid product board include gain adjustment, Wide Dynamic Range Compression (WDRC) with 32 channels, EQ curve with 64 frequency points, dual-microphone beamforming combined with AI-based noise reduction for intelligent fusion noise reduction, achieving an 14.5ms latency, 20dB noise reduction and 5.7mA power consumption. The WTM2101 also features AI transparency, allowing selective transmission of desired sounds such as TV and music. Feedback cancellation is a necessary function of hearing aids. To achieve this, the WTM2101 incorporates both traditional feedback cancellation algorithms and a combination of neural network (NN) anti-feedback algorithms, preventing feedback even at gains of several tens of decibels. In terms of health monitoring, it includes a low-power NN heart rate algorithm and achieves ultra-low power consumption in standard mode at 50uA and 80uA in motion mode.

 

Considering the need for wearer control and convenience within the ear canal, automatic environmental recognition functionality is essential. Based on deep learning/classical algorithms, the WTM2101 incorporates automatic environmental sound recognition and control. With Fbank operations, it enables voice command control of up to a hundred words, with computing power ranging from 200M to 1Gops.

Compared with other chips, WTM2101 has the following advantages in speech recognition:

· Computing in memory architecture: WTM2101 adopts a design based on computing in memory architecture, which tightly integrates storage and computing units, achieving higher data processing efficiency and lower power consumption.

· Multi-model support: WTM2101 supports multiple speech recognition models and algorithms, such as DNN, HMM, etc. Different models can be selected according to different application scenarios to achieve more accurate speech recognition.

· Independent speech front-end processing unit: WTM2101 adopts an independent speech front-end processing unit, which can preprocess and denoise speech signals to improve recognition accuracy and stability.

· Local speech recognition support: WTM2101 supports local speech recognition, without the need for networking, ensuring user privacy and data security.

· Easy to integrate: WTM2101 has open software and hardware interfaces, good customizability and compatibility, and is easy to integrate into various intelligent products.

AI has brought significant upgrades to hearing aids, particularly in intelligent noise reduction, anti-feedback, and environmental recognition. The WTM2101 hearing aid solution based on the storage-computing integrated architecture offers high computing power and low power consumption, making it versatile and capable of customized development, thus accelerating the intelligence of the hearing aid market.

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