Search Results for author:
Found 9 papers, 6 papers with code
MCR-Data2vec 2.0: Improving Self-supervised Speech Pre-training via Model-level Consistency Regularization
Self-supervised learning (SSL) has shown significant progress in speech processing tasks.
EM-Network: Oracle Guided Self-distillation for Sequence Learning
We introduce EM-Network, a novel self-distillation approach that effectively leverages target information for supervised sequence-to-sequence (seq2seq) learning.
Kosp2e: Korean Speech to English Translation Corpus
Most speech-to-text (S2T) translation studies use English speech as a source, which makes it difficult for non-English speakers to take advantage of the S2T technologies.
StyleKQC: A Style-Variant Paraphrase Corpus for Korean Questions and Commands
Paraphrasing is often performed with less concern for controlled style conversion.
Towards an Efficient Code-Mixed Grapheme-to-Phoneme Conversion in an Agglutinative Language: A Case Study on To-Korean Transliteration
Code-mixed grapheme-to-phoneme (G2P) conversion is a crucial issue for modern speech recognition and synthesis task, but has been seldom investigated in sentence-level in literature.
Machines Getting with the Program: Understanding Intent Arguments of Non-Canonical Directives
Modern dialog managers face the challenge of having to fulfill human-level conversational skills as part of common user expectations, including but not limited to discourse with no clear objective.
Investigating an Effective Character-level Embedding in Korean Sentence Classification
Different from the writing systems of many Romance and Germanic languages, some languages or language families show complex conjunct forms in character composition.
On Measuring Gender Bias in Translation of Gender-neutral Pronouns
However, detection and evaluation of gender bias in the machine translation systems are not yet thoroughly investigated, for the task being cross-lingual and challenging to define.
Speech Intention Understanding in a Head-final Language: A Disambiguation Utilizing Intonation-dependency
This paper suggests a system which identifies the inherent intention of a spoken utterance given its transcript, in some cases using auxiliary acoustic features.
