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20172026
most citedCompressing Recurrent Neural Network with Tensor Train

111 citations · 224 across the 31 of their papers we have counts for

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Showing 2020 · cs.CLShow all

7 papers · 2 filters

cs.CL2020★ 9 cited

Simultaneous Speech-to-Speech Translation System with Neural Incremental ASR, MT, and TTS

Katsuhito Sudoh, Takatomo Kano, Sashi Novitasari +3

This paper presents a newly developed, simultaneous neural speech-to-speech translation system and its evaluation. The system consists of three fully-incremental neural processing…

cs.CL2020★ 11 cited

Cross-Lingual Machine Speech Chain for Javanese, Sundanese, Balinese, and Bataks Speech Recognition and Synthesis

Sashi Novitasari, Andros Tjandra, Sakriani Sakti +1

Even though over seven hundred ethnic languages are spoken in Indonesia, the available technology remains limited that could support communication within indigenous communities as…

cs.CL2020

Sequence-to-Sequence Learning via Attention Transfer for Incremental Speech Recognition

Sashi Novitasari, Andros Tjandra, Sakriani Sakti +1

Attention-based sequence-to-sequence automatic speech recognition (ASR) requires a significant delay to recognize long utterances because the output is generated after receiving en…

cs.CL2020★ 1 cited

Incremental Machine Speech Chain Towards Enabling Listening while Speaking in Real-time

Sashi Novitasari, Andros Tjandra, Tomoya Yanagita +2

Inspired by a human speech chain mechanism, a machine speech chain framework based on deep learning was recently proposed for the semi-supervised development of automatic speech re…

cs.CL2020★ 1 cited

Augmenting Images for ASR and TTS through Single-loop and Dual-loop Multimodal Chain Framework

Johanes Effendi, Andros Tjandra, Sakriani Sakti +1

Previous research has proposed a machine speech chain to enable automatic speech recognition (ASR) and text-to-speech synthesis (TTS) to assist each other in semi-supervised learni…

cs.CL2020

The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units

Ewan Dunbar, Julien Karadayi, Mathieu Bernard +6

We present the Zero Resource Speech Challenge 2020, which aims at learning speech representations from raw audio signals without any labels. It combines the data sets and metrics f…