Work

Author response: High-Fidelity Neural Speech Reconstruction through an Efficient Acoustic-Linguistic Dual-Pathway Framework

Year: 2026

Type: peer-review

Abstract: eLife AssessmentThis study presents a valuable advance in reconstructing naturalistic speech from intracranial ECoG data using a dual-pathway model.The evidence supporting the claims of the authors is solid.This work will be of interest to cognitive neuroscientists and computer scientists/engineers working on speech reconstruction from neural data.

Source: eLife

DOI: 10.7554/elife.109400.2.sa0

Authors: Jiawei Li, Chunxu Guo, Chao Zhang, Edward F Chang, Yuanning Li

Institutions: ShanghaiTech University, Shanghai Artificial Intelligence Laboratory, Tsinghua University, University of California, San Francisco

Language: English

Topic: Speech Recognition and Synthesis

Subfield: Artificial Intelligence

Field: Computer Science

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $2,500