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Unsupervised Speaker Adaptation Using Attention-Based Speaker Memory For End-To-End Asr
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Unsupervised Speaker Adaptation Using Attention-Based Speaker Memory For End-To-End Asr
We propose an unsupervised speaker adaptation method inspired by the neural Turing machine for end-to-end (E2E) automatic speech recognition (ASR). The proposed model contains a memory block that holds speaker i-vectors extracted from the training data an
We propose an unsupervised speaker adaptation method inspired by the neural Turing machine for end-to-end (E2E) automatic speech recognition (ASR). The proposed model contains a memory block that holds speaker i-vectors extracted from the training data an
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