sunprinceS/MetaASR-CrossAccent
Meta-Learning for End-to-End ASR
This project helps speech researchers and machine learning engineers pre-train speech recognition models that can adapt to different accents with limited data. It takes audio data and corresponding transcripts for various accents as input, and outputs a pre-trained model capable of recognizing speech across those accents more effectively than standard models. This is for researchers and practitioners working on improving automatic speech recognition (ASR) systems.
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Use this if you are a speech researcher or machine learning engineer focused on building robust ASR systems that perform well across multiple accents, especially in scenarios with limited data for each accent.
Not ideal if you need a ready-to-use ASR application or if your primary goal is general speech recognition without a specific focus on cross-accent adaptation with meta-learning techniques.
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MIT
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Last pushed
Aug 08, 2020
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