1 citations · 2 across the 11 of their papers we have counts for
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Attacking UTMOS: Probing the Robustness of a Speech Quality Assessment Model
Wen-Chin Huang, Tomoki Toda
UTMOS has become one of the most commonly used deep neural network-based speech quality assessment (SQA) metrics in speech processing research. In this paper, we attack UTMOS to pr…
PathBench: Speech Intelligibility Benchmark for Automatic Pathological Speech Assessment
Bence Mark Halpern, Thomas Tienkamp, Defne Abur +1
Automatic speech intelligibility assessment is crucial for monitoring speech disorders and therapy efficacy. However, existing methods are difficult to compare: research is fragmen…
Exploring Pre-training Benefits on Phoneme Addition through Fine-tuning in Speech Synthesis
Masato Murata, Koichi Miyazaki, Tomoki Koriyama +1
Transfer learning is widely used for low-resource text-to-speech. When the target corpus contains phonemes unseen in pre-training, the model must expand its phoneme inventory durin…
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.…
An Extensive Analysis of the Singing Voice Conversion Challenge 2025 Evaluation Results
Lester Phillip Violeta, Xueyao Zhang, Jiatong Shi +4
We present a thorough analysis of the findings of the latest iteration of the Singing Voice Conversion Challenge, a scientific event aiming to compare and understand different voic…
MOS-Bench: Benchmarking Generalization Abilities of Subjective Speech Quality Assessment Models
Wen-Chin Huang, Erica Cooper, Tomoki Toda
In this paper, we study the task of subjective speech quality assessment (SSQA), which refers to predicting the perceptual quality of speech. Owing to the development of deep neura…