111 citations · 391 across the 44 of their papers we have counts for
6 papers · 1 filter
End-to-End Feedback Loss in Speech Chain Framework via Straight-Through Estimator
Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
The speech chain mechanism integrates automatic speech recognition (ASR) and text-to-speech synthesis (TTS) modules into a single cycle during training. In our previous work, we ap…
Multi-scale Alignment and Contextual History for Attention Mechanism in Sequence-to-sequence Model
Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
A sequence-to-sequence model is a neural network module for mapping two sequences of different lengths. The sequence-to-sequence model has three core modules: encoder, decoder, and…
Machine Speech Chain with One-shot Speaker Adaptation
Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
In previous work, we developed a closed-loop speech chain model based on deep learning, in which the architecture enabled the automatic speech recognition (ASR) and text-to-speech…
Interactive Image Manipulation with Natural Language Instruction Commands
Seitaro Shinagawa, Koichiro Yoshino, Sakriani Sakti +2
We propose an interactive image-manipulation system with natural language instruction, which can generate a target image from a source image and an instruction that describes the d…
Structured-based Curriculum Learning for End-to-end English-Japanese Speech Translation
Takatomo Kano, Sakriani Sakti, Satoshi Nakamura
Sequence-to-sequence attentional-based neural network architectures have been shown to provide a powerful model for machine translation and speech recognition. Recently, several wo…
Tensor Decomposition for Compressing Recurrent Neural Network
Andros Tjandra, Sakriani Sakti, Satoshi Nakamura
In the machine learning fields, Recurrent Neural Network (RNN) has become a popular architecture for sequential data modeling. However, behind the impressive performance, RNNs requ…