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Found 9 papers, 4 papers with code
GiBERT: Enhancing BERT with Linguistic Information using a Lightweight Gated Injection Method
Large pre-trained language models such as BERT have been the driving force behind recent improvements across many NLP tasks.
A Comparative Analysis of Pretrained Language Models for Text-to-Speech
In this study, we aim to address this gap by conducting a comparative analysis of different PLMs for two TTS tasks: prosody prediction and pause prediction.
eCat: An End-to-End Model for Multi-Speaker TTS & Many-to-Many Fine-Grained Prosody Transfer
We show that eCat statistically significantly reduces the gap in naturalness between CopyCat2 and human recordings by an average of 46. 7% across 2 languages, 3 locales, and 7 speakers, along with better target-speaker similarity in FPT.
GiBERT: Introducing Linguistic Knowledge into BERT through a Lightweight Gated Injection Method
Large pre-trained language models such as BERT have been the driving force behind recent improvements across many NLP tasks.
Better Early than Late: Fusing Topics with Word Embeddings for Neural Question Paraphrase Identification
Question paraphrase identification is a key task in Community Question Answering (CQA) to determine if an incoming question has been previously asked.
tBERT: Topic Models and BERT Joining Forces for Semantic Similarity Detection
Semantic similarity detection is a fundamental task in natural language understanding.
Aiming beyond the Obvious: Identifying Non-Obvious Cases in Semantic Similarity Datasets
Existing datasets for scoring text pairs in terms of semantic similarity contain instances whose resolution differs according to the degree of difficulty.
ClassifierGuesser: A Context-based Classifier Prediction System for Chinese Language Learners
Classifiers are function words that are used to express quantities in Chinese and are especially difficult for language learners.
Automatically Suggesting Example Sentences of Near-Synonyms for Language Learners
In this paper, we propose GiveMeExample that ranks example sentences according to their capacity of demonstrating the differences among English and Chinese near-synonyms for language learners.
