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Murali Karthick Baskar

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Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling

2018 · arXiv (Cornell University)

Sequence-to-sequence (seq2seq) approach for low-resource ASR is a relatively new direction in speech research. The approach benefits by performing model training without using lexicon and alignments. However, this poses a new problem of requiring more …
Eat: Enhanced ASR-TTS for Self-Supervised Speech Recognition

2021

Self-supervised ASR-TTS models suffer in out-of-domain data conditions. Here we propose an enhanced ASR-TTS (EAT) model that incorporates two main features: 1) The ASR→TTS direction is equipped with a language model reward to penalize the …