Papers

BrainTalker: Low-Resource Brain-to-Speech Synthesis with Transfer Learning using Wav2Vec 2.0

International Conference
2021~
작성자
dsp
작성일
2023-08-11 11:32
조회
1803
Authors : Miseul Kim, Zhenyu Piao, Jihyun Lee, Hong-Goo Kang

Year : 2023

Publisher / Conference : The IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI)

Research area : Speech Signal Processing, Etc


Presentation : Poster

Decoding spoken speech from neural activity in the brain is a fast-emerging research topic, as it could enable communication for people who have difficulties with producing audible speech. For this task, electrocorticography (ECoG) is a common method for recording brain activity with high temporal resolution and high spatial precision. However, due to the risky surgical procedure required for obtaining ECoG recordings, relatively little of this data has been collected, and the amount is insufficient to train a neural network-based Brain-to-Speech (BTS) system. To address this problem, we propose BrainTalker—a novel BTS framework that generates intelligible spoken speech from ECoG signals under extremely low-resource scenarios. We apply a transfer learning approach utilizing a pre-trained self-supervised model, Wav2Vec 2.0. Specifically, we train an encoder module to map ECoG signals to latent embeddings that match Wav2Vec 2.0 representations of the corresponding spoken speech. These embeddings are then transformed into mel-spectrograms using stacked convolutional and transformer-based layers, which are fed into a neural vocoder to synthesize speech waveform. Experimental results demonstrate our proposed framework achieves outstanding performance in terms of subjective and objective metrics, including a Pearson correlation coefficient of 0.9 between generated and ground truth mel-spectrograms. We share publicly available Demos and Code.
전체 367
347 International Conference Zhenyu Piao, Hyungseob Lim, Miseul Kim, Hong-goo Kang "PDF-NET: Pitch-adaptive Dynamic Filter Network for Intra-gender Speaker Verification" in APSIPA ASC, 2023
346 International Conference WooSeok Ko, Seyun Um, Zhenyu Piao, Hong-goo Kang "Consideration of Varying Training Lengths for Short-Duration Speaker Verification" in APSIPA ASC, 2023
345 International Journal Hyungchan Yoon, Changhwan Kim, Seyun Um, Hyun-Wook Yoon, Hong-Goo Kang "SC-CNN: Effective Speaker Conditioning Method for Zero-Shot Multi-Speaker Text-to-Speech Systems" in IEEE Signal Processing Letters, vol.30, pp.593-597, 2023
344 International Conference Miseul Kim, Zhenyu Piao, Jihyun Lee, Hong-Goo Kang "BrainTalker: Low-Resource Brain-to-Speech Synthesis with Transfer Learning using Wav2Vec 2.0" in The IEEE-EMBS International Conference on Biomedical and Health Informatics (BHI), 2023
343 International Conference Seyun Um, Jihyun Kim, Jihyun Lee, Hong-Goo Kang "Facetron: A Multi-speaker Face-to-Speech Model based on Cross-Modal Latent Representations" in EUSIPCO, 2023
342 International Conference Hejung Yang, Hong-Goo Kang "Feature Normalization for Fine-tuning Self-Supervised Models in Speech Enhancement" in INTERSPEECH, 2023
341 International Conference Jihyun Kim, Hong-Goo Kang "Contrastive Learning based Deep Latent Masking for Music Source Seperation" in INTERSPEECH, 2023
340 International Conference Woo-Jin Chung, Doyeon Kim, Soo-Whan Chung, Hong-Goo Kang "MF-PAM: Accurate Pitch Estimation through Periodicity Analysis and Multi-level Feature Fusion" in INTERSPEECH, 2023
339 International Conference Hyungchan Yoon, Seyun Um, Changhwan Kim, Hong-Goo Kang "Adversarial Learning of Intermediate Acoustic Feature for End-to-End Lightweight Text-to-Speech" in INTERSPEECH, 2023
338 International Conference Hyungchan Yoon, Changhwan Kim, Eunwoo Song, Hyun-Wook Yoon, Hong-Goo Kang "Pruning Self-Attention for Zero-Shot Multi-Speaker Text-to-Speech" in INTERSPEECH, 2023