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Improving Speech Recognition on Augmented Reality Glasses with Hybrid Datasets Using Deep Learning: A Simulation-Based Approach
Practical Solutions and Value:
Google AI researchers have developed a method that combines sound separation and automatic speech recognition (ASR) to improve speech recognition on augmented reality (AR) glasses, especially in noisy and reverberant environments. This advancement aims to enhance communication experiences, particularly for individuals with hearing impairments or conversing in non-native languages.
The traditional methods face challenges in separating speech from background noise and other speakers, prompting the need for innovative approaches.
The proposed practical solution involves leveraging a room simulator to generate simulated training data, which complements real-world data collected from AR glasses. This approach captures the unique acoustic properties of the AR glasses while enhancing model performance.
Experimental results demonstrate significant improvement in speech recognition performance when using the hybrid dataset, consisting of both real-world and simulated data. The proposed method offers a cost-effective solution for making speech recognition systems for wearable devices.
How AI Can Redefine Your Way of Work:
– Identify Automation Opportunities: Locate key customer interaction points that can benefit from AI.
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