1 citations · 1 across the 6 of their papers we have counts for
7 papers
Multimodal Contrastive Representation Learning Based Voice Conversion for Electrolaryngeal Speech Enhancement
Ding Ma, Jinyi Mi, Jiajun He +3
Electrolaryngeal (EL) speech suffers from severe acoustic mismatches with normal speech, resulting in degraded naturalness and intelligibility. These mismatches also make sequence-…
Learning Emotion-discriminative Representations for Zero-Shot Cross-lingual Speech Emotion Recognition
Jinyi Mi, Ding Ma, Tomoki Toda
Zero-shot cross-lingual speech emotion recognition (SER) remains challenging due to distribution mismatches across languages and the lack of emotion annotations in target language.…
Advancing Electrolaryngeal Speech Enhancement Through Speech-Text Representation Learning
Ding Ma, Jinyi Mi, Fengji Li +5
Objective: laryngectomees depend on an electromechanical device to generate electrolaryngeal (EL) speech. Compared with normal speech, EL speech suffers from severe distortion, lim…
M4SER: Multimodal, Multirepresentation, Multitask, and Multistrategy Learning for Speech Emotion Recognition
Jiajun He, Xiaohan Shi, Cheng-Hung Hu +3
Multimodal speech emotion recognition (SER) has emerged as pivotal for improving human-machine interaction. Researchers are increasingly leveraging both speech and textual informat…
GIA-MIC: Multimodal Emotion Recognition with Gated Interactive Attention and Modality-Invariant Learning Constraints
Jiajun He, Jinyi Mi, Tomoki Toda
Multimodal emotion recognition (MER) extracts emotions from multimodal data, including visual, speech, and text inputs, playing a key role in human-computer interaction. Attention-…
Improved Architecture for High-resolution Piano Transcription to Efficiently Capture Acoustic Characteristics of Music Signals
Jinyi Mi, Sehun Kim, Tomoki Toda
Automatic music transcription (AMT), aiming to convert musical signals into musical notation, is one of the important tasks in music information retrieval. Recently, previous works…
Two-stage Framework for Robust Speech Emotion Recognition Using Target Speaker Extraction in Human Speech Noise Conditions
Jinyi Mi, Xiaohan Shi, Ding Ma +3
Developing a robust speech emotion recognition (SER) system in noisy conditions faces challenges posed by different noise properties. Most previous studies have not considered the…