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Lin-shan Lee

3 أوراق في مجموعة PaperMetrix

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أوراق هذا المؤلف

  1. Towards End-to-end Speech-to-text Translation with Two-pass Decoding

    2019

    Speech-to-text translation (ST) refers to transforming the audio in source language to the text in target language. Mainstream solutions for such tasks are to cascade automatic speech recognition with machine translation, for which the transcriptions …

  2. Order-Preserving Abstractive Summarization for Spoken Content Based on Connectionist Temporal Classification

    2017

    Connectionist temporal classification (CTC) is a powerful approach for sequence-to-sequence learning, and has been popularly used in speech recognition.The central ideas of CTC include adding a label "blank" during training.With this mechanism, CTC eliminates the …

  3. Towards Unsupervised Speech Recognition and Synthesis with Quantized Speech Representation Learning

    2020

    In this paper we propose a Sequential Representation Quantization AutoEncoder (SeqRQ-AE) to learn from primarily unpaired audio data and produce sequences of representations very close to phoneme sequences of speech utterances. This is achieved by …