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本项目将《动手学深度学习》(Dive into Deep Learning)原书中的MXNet实现改为PyTorch实现。
《动手学深度学习》习题解答，在线阅读地址如下：
《动手学深度学习》：面向中文读者、能运行、可讨论。中英文版被70多个国家的500多所大学用于教学。
Neural building blocks for speaker diarization: speech activity detection, speaker change detection, overlapped speech detection, speaker embedding
Awesome speech/audio LLMs, representation learning, and codec models
Learn OpenCV : C++ and Python Examples
李宏毅2021/2022/2023春季机器学习课程课件及作业
DOSE: Diffusion Dropout with Adaptive Prior for Speech Enhancement, Conference on Neural Information Processing Systems (NeurIPS), 2023
PyTorch Implementation of "Monotonic Chunkwise Attention" (ICLR 2018)
Code for "Online and Linear Time Attention by Enforcing Monotonic Alignments"
此DEMO为webrtc中AEC3模块单独扣出,并使用远端参考信号和近端信号两个.wav文件进行测试，输出经过AEC3处理后的.wav音频文件。
Awesome-LLM: a curated list of Large Language Model
Acoustic Echo Cancellation with Nerual Kalman Filtering
机器人视觉 移动机器人 VS-SLAM ORB-SLAM2 深度学习目标检测 yolov3 行为检测 opencv PCL 机器学习 无人驾驶
The official gpt4free repository | various collection of powerful language models
