2 citations · 2 across the 2 of their papers we have counts for
5 papers
Back from the future: bidirectional CTC decoding using future information in speech recognition
Namkyu Jung, Geonmin Kim, Han-Gyu Kim
In this paper, we propose a simple but effective method to decode the output of Connectionist Temporal Classifier (CTC) model using a bi-directional neural language model. The bidi…
Spell my name: keyword boosted speech recognition
Namkyu Jung, Geonmin Kim, Joon Son Chung
Recognition of uncommon words such as names and technical terminology is important to understanding conversations in context. However, the ability to recognise such words remains a…
Semi-supervised Disentanglement with Independent Vector Variational Autoencoders
Bo-Kyeong Kim, Sungjin Park, Geonmin Kim +1
We aim to separate the generative factors of data into two latent vectors in a variational autoencoder. One vector captures class factors relevant to target classification tasks, w…
Unpaired Speech Enhancement by Acoustic and Adversarial Supervision for Speech Recognition
Geonmin Kim, Hwaran Lee, Bo-Kyeong Kim +2
Many speech enhancement methods try to learn the relationship between noisy and clean speech, obtained using an acoustic room simulator. We point out several limitations of enhance…
Compositional Sentence Representation from Character within Large Context Text
Geonmin Kim, Hwaran Lee, Jisu Choi +1
This paper describes a Hierarchical Composition Recurrent Network (HCRN) consisting of a 3-level hierarchy of compositional models: character, word and sentence. This model is desi…