Torchaudio Transforms. Sep 5, 2025 · 本文详细介绍了使用PyTorch的torchaud

Sep 5, 2025 · 本文详细介绍了使用PyTorch的torchaudio库进行音频数据的读取、预处理、数据增强、特征提取和保存。 涵盖了从加载不同格式的音频文件、进行数据增强（如混响、噪声添加）到提取梅尔频谱图、MFCC等特征，以及使用Griffin-Lim算法进行频域到时域的转换。 Nov 18, 2025 · 文章浏览阅读3w次，点赞26次，收藏103次。本文详细介绍使用torchaudio库进行音频文件加载、波形显示、频谱图生成及多种音频转换方法，如重采样、Mu-Law编码与解码，并展示了与Kaldi工具包的兼容性。 Fade class torchaudio. html> __ for more information. (Default: ``400``) win_length (int or None, optional): Window size. It minimizes the euclidian norm between the input mel-spectrogram and the Nov 30, 2023 · transforms. nn. transforms 模块包含常见的音频处理和特征提取。下图显示了可用的部分变换之间的关系。 Author: Moto Hira torchaudio implements feature extractions commonly used in the audio domain. (Default: 128) sample_rate (int Jan 15, 2025 · This means torchaudio transforms can be used in Compose now. (Default: ``n_fft``) hop_length (int or None, optional): Length AmplitudeToDB class torchaudio. By supporting PyTorch, torchaudio follows the same philosophy of providing strong GPU acceleration, having a focus on trainable features through the autograd system, and having consistent style (tensor names and dimension names). Optional [int] = None, hop_length: ~typing.

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