Sakriani Sakti

Professor

Nara Institute of Science and Technology

Japan

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Professor Sakriani Sakti is a faculty member at the Nara Institute of Science and Technology in Japan. His research areas include speech processing, speech synthesis, and machine translation, focusing on applications for low-resourced languages and adaptive systems. Recent publications highlight innovative approaches in transcription, cross-lingual translation, and the development of neural frameworks for text-to-speech synthesis.

Sakriani Sakti

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Articles (15)

Toward fast meeting transcription: NAIST system for CHiME-8 NOTSOFAR-1 task and its analysis

ZeST: A Zero-Resourced Speech-to-Speech Translation Approach for Unknown, Unpaired, and Untranscribed Languages

Zero-Shot Cross-Lingual Text-to-Speech With Style-Enhanced Normalization and Auditory Feedback Training Mechanism

Applying Syntax-Prosody Mapping Hypothesis and Boundary-Driven Theory to Neural Sequence-to-Sequence Speech Synthesis

MAG-BERT-ARL for Fair Automated Video Interview Assessment

Japanese Neural Incremental Text-to-Speech Synthesis Framework With an Accent Phrase Input

A Machine Speech Chain Approach for Dynamically Adaptive Lombard TTS in Static and Dynamic Noise Environments

Modeling Unsupervised Empirical Adaptation by DPGMM and DPGMM-RNN Hybrid Model to Extract Perceptual Features for Low-Resource ASR

End-to-End Image-to-Speech Generation for Untranscribed Unknown Languages

Instance-Level Heterogeneous Domain Adaptation for Limited-Labeled Sketch-to-Photo Retrieval

Multimodal Chain: Cross-Modal Collaboration Through Listening, Speaking, and Visualizing

Tackling Perception Bias in Unsupervised Phoneme Discovery Using DPGMM-RNN Hybrid Model and Functional Load

Corrections to “Machine Speech Chain” [Mar 20 976-989]

End-to-End Speech Translation With Transcoding by Multi-Task Learning for Distant Language Pairs

Machine Speech Chain

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Candy Olivia Mawalim

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