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Nianzu Zheng

2 accepted papers

2023

Improving End-to-End Speech Processing by Efficient Text Data Utilization with Latent Synthesis

EMNLP 2023long findings

Training a high performance end-to-end speech (E2E) processing model requires an enormous amount of labeled speech data, especially in the era of data-centric artificial intelligence. However, labeled speech data are usually scarcer and more expensive for collection, compared to textual data. We pro…

Cited by 0SourceScholar
2021

Fcl-Taco2: Towards Fast, Controllable and Lightweight Text-to-Speech Synthesis

ICASSP 2021accepted

Sequence-to-sequence (seq2seq) learning has greatly improved text-to-speech (TTS) synthesis performance, but effective implementation on resource-restricted devices remains challenging as seq2seq models are usually computationally expensive and memory intensive. To achieve fast inference speed and s…

Cited by 0SourceScholar