Yosuke Higuchi

About Yosuke Higuchi

Yosuke Higuchi, With an exceptional h-index of 13 and a recent h-index of 13 (since 2020), a distinguished researcher at Waseda University, specializes in the field of speech recognition.

His recent articles reflect a diverse array of research interests and contributions to the field:

Parody Detection Using Source-Target Attention with Teacher-Forced Lyrics

Mask-Conformer: Augmenting Conformer with Mask-Predict Decoder

Segment-Level Vectorized Beam Search Based on Partially Autoregressive Inference

Harnessing the Zero-Shot Power of Instruction-Tuned Large Language Model in End-to-End Speech Recognition

Spotting Parodies: Detecting Alignment Collapse Between Lyrics and Singing Voice

Mask-CTC-based Encoder Pre-training for Streaming End-to-End Speech Recognition

Parody Detection Based on Alignment Collapse Between Lyrics and Singing Voice

Bectra: Transducer-based end-to-end asr with bert-enhanced encoder

Yosuke Higuchi Information

University

Position

___

Citations(all)

704

Citations(since 2020)

702

Cited By

42

hIndex(all)

13

hIndex(since 2020)

13

i10Index(all)

14

i10Index(since 2020)

14

Email

University Profile Page

Google Scholar

Yosuke Higuchi Skills & Research Interests

speech recognition

Top articles of Yosuke Higuchi

Parody Detection Using Source-Target Attention with Teacher-Forced Lyrics

2024/4/14

Mask-Conformer: Augmenting Conformer with Mask-Predict Decoder

2023/12/16

Segment-Level Vectorized Beam Search Based on Partially Autoregressive Inference

2023/12/16

Harnessing the Zero-Shot Power of Instruction-Tuned Large Language Model in End-to-End Speech Recognition

arXiv preprint arXiv:2309.10524

2023/9/19

Spotting Parodies: Detecting Alignment Collapse Between Lyrics and Singing Voice

2023/9

Mask-CTC-based Encoder Pre-training for Streaming End-to-End Speech Recognition

2023/9

Parody Detection Based on Alignment Collapse Between Lyrics and Singing Voice

IEICE Technical Report; IEICE Tech. Rep.

2023/6/16

Bectra: Transducer-based end-to-end asr with bert-enhanced encoder

2023/6/4

Intermpl: Momentum Pseudo-Labeling With Intermediate CTC Loss

2023/6/4

Metric learning of speaker diarization

2023/5/16

A study on the integration of pre-trained ssl, asr, lm and slu models for spoken language understanding

2023/1/9

BERT meets CTC: New formulation of end-to-end speech recognition with pre-trained masked language model

arXiv preprint arXiv:2210.16663

2022/12

CTC alignments improve autoregressive translation

arXiv preprint arXiv:2210.05200

2022/10/11

Momentum pseudo-labeling: Semi-supervised asr with continuously improving pseudo-labels

IEEE Journal of Selected Topics in Signal Processing

2022/8/1

Yosuke Higuchi
Yosuke Higuchi

H-Index: 3

Improving non-autoregressive end-to-end speech recognition with pre-trained acoustic and language models

2022/5/23

Shinji Watanabe
Shinji Watanabe

H-Index: 45

Yosuke Higuchi
Yosuke Higuchi

H-Index: 3

Advancing momentum pseudo-labeling with conformer and initialization strategy

2022/5/23

Yosuke Higuchi
Yosuke Higuchi

H-Index: 3

Hierarchical conditional end-to-end asr with ctc and multi-granular subword units

2022/5/23

An investigation of enhancing CTC model for triggered attention-based streaming ASR

2021/12

A comparative study on non-autoregressive modelings for speech-to-text generation

2021/12/13

Non-autoregressive end-to-end speech translation with parallel autoregressive rescoring

arXiv preprint arXiv:2109.04411

2021/9/9

See List of Professors in Yosuke Higuchi University(Waseda University)