Rishit-dagli/Conformer
An implementation of Conformer: Convolution-augmented Transformer for Speech Recognition, a Transformer Variant in TensorFlow/Keras
This project provides an implementation of Conformer, a state-of-the-art neural network architecture designed for speech recognition. It takes raw audio sequences as input and processes them to improve the accuracy of speech-to-text conversion. This is ideal for machine learning engineers and researchers working on building or improving automated speech recognition (ASR) systems.
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Use this if you are a machine learning engineer or researcher developing advanced speech recognition models and need a robust, high-performance building block in TensorFlow/Keras.
Not ideal if you are looking for a pre-trained, ready-to-use speech-to-text API or a tool for general audio processing tasks.
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Language
Python
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Apache-2.0
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Last pushed
Jan 20, 2022
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