5 papers
Aligning MusicLLM with Emotion using Instruction Tuning and Feedback-Driven Alignment
Takuya Hasumi, Welly Naptali
This paper investigates whether music large language models (MusicLLMs) can be aligned for emotion regression. While MusicLLMs have shown strong performance in music information re…
DnR-nonverbal: Cinematic Audio Source Separation Dataset Containing Non-Verbal Sounds
Takuya Hasumi, Yusuke Fujita
We propose a new dataset for cinematic audio source separation (CASS) that handles non-verbal sounds. Existing CASS datasets only contain reading-style sounds as a speech stem. The…
BitTTS: Highly Compact Text-to-Speech Using 1.58-bit Quantization and Weight Indexing
Masaya Kawamura, Takuya Hasumi, Yuma Shirahata +1
This paper proposes a highly compact, lightweight text-to-speech (TTS) model for on-device applications. To reduce the model size, the proposed model introduces two techniques. Fir…
Music Tagging with Classifier Group Chains
Takuya Hasumi, Tatsuya Komatsu, Yusuke Fujita
We propose music tagging with classifier chains that model the interplay of music tags. Most conventional methods estimate multiple tags independently by treating them as multiple…
LibriTTS-P: A Corpus with Speaking Style and Speaker Identity Prompts for Text-to-Speech and Style Captioning
Masaya Kawamura, Ryuichi Yamamoto, Yuma Shirahata +2
We introduce LibriTTS-P, a new corpus based on LibriTTS-R that includes utterance-level descriptions (i.e., prompts) of speaking style and speaker-level prompts of speaker characte…