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Found 5 papers, 1 papers with code
The Hitachi-JHU DIHARD III System: Competitive End-to-End Neural Diarization and X-Vector Clustering Systems Combined by DOVER-Lap
This paper provides a detailed description of the Hitachi-JHU system that was submitted to the Third DIHARD Speech Diarization Challenge.
HATSUKI : An anime character like robot figure platform with anime-style expressions and imitation learning based action generation
Although numerous robots have been developed, less have focused on otaku-culture or on embodying the anime character figurine.
Action Generation
Cultural Vocal Bursts Intensity Prediction
+1
CNN-based MultiChannel End-to-End Speech Recognition for everyday home environments
By employing a convolutional neural network (CNN)-based multichannel end-to-end speech recognition system, this study attempts to overcome the presents difficulties in everyday environments.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling
In this work, we attempt to use data from 10 BABEL languages to build a multi-lingual seq2seq model as a prior model, and then port them towards 4 other BABEL languages using transfer learning approach.
Language Modelling
Sequence-To-Sequence Speech Recognition
+2
Weakly Supervised Deep Recurrent Neural Networks for Basic Dance Step Generation
However, applying DNNs for generating dance to a piece of music is nevertheless challenging, because of 1) DNNs need to generate large sequences while mapping the music input, 2) the DNN needs to constraint the motion beat to the music, and 3) DNNs require a considerable amount of hand-crafted data.
