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Neural network processing delivering exceptional performance, efficiency, and real-time responsiveness with minimal computational demands. Alango's neural network processing design concept integrates classical pre and post-processing techniques that have been refined over years of experience in voice preprocessing. This fusion of traditional methods with neural networks forms the foundation of an efficient deep learning convolution network structure, meticulously designed and trained using TensorFlow tools. The utilization of Compact Convolutional Neural Networks ensures not only high performance but also efficient implementation. Furthermore, Alango's solution is characterized by its support for low and ultra-low latency applications, making it ideal for applications demanding real-time responsiveness. Remarkably, it achieves all of this with minimal computational resource requirements, both in terms of processing power (MIPS) and memory. Additionally, its compatibility with TensorFlow Lite and TensorFlow Micro facilitates seamless porting, while the incorporation of classical pre/post processing algorithms with DNN further enhances its overall effectiveness. |
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NOISE SUPPRESSION NEURAL NETWORKS
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DEREVERBERATION NEURAL NETWORKS
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