3 citations · 6 across the 5 of their papers we have counts for
4 papers · 1 filter
Leveraging Parameter-Efficient Transfer Learning for Multi-Lingual Text-to-Speech Adaptation
Yingting Li, Ambuj Mehrish, Bryan Chew +2
Different languages have distinct phonetic systems and vary in their prosodic features making it challenging to develop a Text-to-Speech (TTS) model that can effectively synthesise…
HyperTTS: Parameter Efficient Adaptation in Text to Speech using Hypernetworks
Yingting Li, Rishabh Bhardwaj, Ambuj Mehrish +2
Neural speech synthesis, or text-to-speech (TTS), aims to transform a signal from the text domain to the speech domain. While developing TTS architectures that train and test on th…
Making Pre-trained Language Models Better Continual Few-Shot Relation Extractors
Shengkun Ma, Jiale Han, Yi Liang +1
Continual Few-shot Relation Extraction (CFRE) is a practical problem that requires the model to continuously learn novel relations while avoiding forgetting old ones with few label…
Exploring Task Difficulty for Few-Shot Relation Extraction
Jiale Han, Bo Cheng, Wei Lu
Few-shot relation extraction (FSRE) focuses on recognizing novel relations by learning with merely a handful of annotated instances. Meta-learning has been widely adopted for such…