4 papers · 1 filter
Do speech foundation models perceive speaker similarity as humans do?
Minoru Kishi, Hayato Yagi, Shinnosuke Takamichi +1
This study presents a comparative analysis between the speaker embeddings of speech foundation models and human subjective perception of speaker similarity. Human listeners have th…
Spatial-CLAP: Learning Spatially-Aware audio--text Embeddings for Multi-Source Conditions
Kentaro Seki, Yuki Okamoto, Kouei Yamaoka +3
Contrastive language--audio pretraining (CLAP) has achieved remarkable success as an audio--text embedding framework, but existing approaches are limited to monaural or single-sour…
RELATE: Subjective evaluation dataset for automatic evaluation of relevance between text and audio
Yusuke Kanamori, Yuki Okamoto, Taisei Takano +3
In text-to-audio (TTA) research, the relevance between input text and output audio is an important evaluation aspect. Traditionally, it has been evaluated from both subjective and…
Construction and Analysis of Impression Caption Dataset for Environmental Sounds
Yuki Okamoto, Ryotaro Nagase, Minami Okamoto +4
Some datasets with the described content and order of occurrence of sounds have been released for conversion between environmental sound and text. However, there are very few texts…