Shypd.aiThe largest open index of AI toolsConformer is an open-source PyTorch implementation of the Conformer model for speech recognition. It combines CNNs and Transformers to efficiently model local and global dependencies in audio sequences.
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Conformer is an unofficial PyTorch implementation of the "Conformer: Convolution-augmented Transformer for Speech Recognition" model, originally presented at INTERSPEECH 2020. This tool is designed to leverage both Convolutional Neural Networks (CNNs) for local feature extraction and Transformers for capturing global interactions within audio sequences. By combining these architectures, Conformer achieves state-of-the-art accuracies in speech recognition tasks while maintaining parameter efficiency. The repository provides the core model code, allowing developers and researchers to integrate and train Conformer within their own speech processing pipelines. It requires Python 3.7 or higher, along with Numpy and PyTorch, and can be installed from the source code.
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