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cs.SD2025
Grapheme-Coherent Phonemic and Prosodic Annotation of Speech by Implicit and Explicit Grapheme Conditioning
Hien Ohnaka, Yuma Shirahata, Byeongseon Park +1
We propose a model to obtain phonemic and prosodic labels of speech that are coherent with graphemes. Unlike previous methods that simply fine-tune a pre-trained ASR model with the…
eess.AS2025
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…