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How Should We Evaluate Naturalness for Synthetic Speech with a Foreign Accent?
Kentaro Onda, Satoru Fukayama, Daisuke Saito +1
Recent advances in speech synthesis technology have enabled the generation of speech with diverse characteristics. One such characteristic is a foreign accent. In our preliminary e…
Subphonetic Acoustic Modeling via Optimal Transport for Pronunciation Assessment
Haopeng Geng, Jiun-Ting Li, Daisuke Saito +1
Pronunciation assessment requires acoustic evidence that is temporally precise, diagnostically meaningful, and faithful to the learner's actual production. However, existing acoust…
Self-supervised Speech Comparison for L2 Phone, Rhythm, and Intonation Scoring
Stephen McIntosh, Reuben Smit, Daisuke Saito +2
L2 speech assessment has traditionally focused on phonetic assessment, leaving the scoring of suprasegmental features such as rhythm and intonation underexplored. Moreover, assessm…
Phone Segmentation and Recognition through Phonological Activation Mapping
Shikhar Bharadwaj, Kwanghee Choi, Stephen McIntosh +8
Phone segmentation and recognition are inherently related tasks, yet modern approaches typically model them separately. We argue that phonetic structure is already latent in the re…
Speech Playground: An Interactive Tool for Speech Analysis and Comparison
Stephen McIntosh, Daisuke Saito, Nobuaki Minematsu
This paper presents Speech Playground, an interactive speech visualization and comparison tool. While existing tools such as Praat are excellent, it can be cumbersome to integrate…
Beyond Acoustic Sparsity and Linguistic Bias: A Prompt-Free Paradigm for Mispronunciation Detection and Diagnosis
Haopeng Geng, Longfei Yang, Xi Chen +3
Mispronunciation Detection and Diagnosis (MDD) requires modeling fine-grained acoustic deviations. However, current ASR-derived MDD systems often face inherent limitations. In part…
Prosodic ABX: A Language-Agnostic Method for Measuring Prosodic Contrast in Speech Representations
Haitong Sun, Stephen McIntosh, Kwanghee Choi +3
Speech representations from self-supervised speech models (S3Ms) are known to be sensitive to phonemic contrasts, but their sensitivity to prosodic contrasts has not been directly…
Kanade: A Simple Disentangled Tokenizer for Spoken Language Modeling
Zhijie Huang, Stephen McIntosh, Daisuke Saito +1
A good language model starts with a good tokenizer. Tokenization is especially important for speech modeling, which must handle continuous signals that mix linguistic and non-lingu…
Advanced Modeling of Interlanguage Speech Intelligibility Benefit with L1-L2 Multi-Task Learning Using Differentiable K-Means for Accent-Robust Discrete Token-Based ASR
Kentaro Onda, Satoru Fukayama, Daisuke Saito +1
Building ASR systems robust to foreign-accented speech is an important challenge in today's globalized world. A prior study explored the way to enhance the performance of phonetic…