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20172026
most citedTransformer-based Acoustic Modeling for Hybrid Speech Recognition

261 citations · 682 across the 43 of their papers we have counts for

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Showing 2020Show all

6 papers · 1 filter

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

Unsupervised Learning of Disentangled Speech Content and Style Representation

Andros Tjandra, Ruoming Pang, Yu Zhang +1

We present an approach for unsupervised learning of speech representation disentangling contents and styles. Our model consists of: (1) a local encoder that captures per-frame info…

cs.CL2020

Transformer VQ-VAE for Unsupervised Unit Discovery and Speech Synthesis: ZeroSpeech 2020 Challenge

Andros Tjandra, Sakriani Sakti, Satoshi Nakamura

In this paper, we report our submitted system for the ZeroSpeech 2020 challenge on Track 2019. The main theme in this challenge is to build a speech synthesizer without any textual…