2 citations · 2 across the 4 of their papers we have counts for
4 papers
A Comparative Analysis of Pretrained Language Models for Text-to-Speech
Marcel Granero-Moya, Penny Karanasou, Sri Karlapati +4
State-of-the-art text-to-speech (TTS) systems have utilized pretrained language models (PLMs) to enhance prosody and create more natural-sounding speech. However, while PLMs have b…
eCat: An End-to-End Model for Multi-Speaker TTS & Many-to-Many Fine-Grained Prosody Transfer
Ammar Abbas, Sri Karlapati, Bastian Schnell +7
We present eCat, a novel end-to-end multispeaker model capable of: a) generating long-context speech with expressive and contextually appropriate prosody, and b) performing fine-gr…
GiBERT: Introducing Linguistic Knowledge into BERT through a Lightweight Gated Injection Method
Nicole Peinelt, Marek Rei, Maria Liakata
Large pre-trained language models such as BERT have been the driving force behind recent improvements across many NLP tasks. However, BERT is only trained to predict missing words…
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification
Nicole Peinelt, Dong Nguyen, Maria Liakata
Question paraphrase identification is a key task in Community Question Answering (CQA) to determine if an incoming question has been previously asked. Many current models use word…