4 papers · 1 filter
Neural Audio Codec with Adjustable Token Temporal Resolution Using Sampling-Frequency-Independent Convolutional Layers
Tomohiko Nakamura, Wataru Nakata, Kanami Imamura +1
Discrete tokens obtained from neural audio codecs (NACs) have been used as compact representations in audio generation and understanding models. In such token-based systems, token…
CraBERT: Efficient Phoneme Encoder Pre-Training via Cascade Fusion of Subword Representations for Text-to-Speech
Dong Yang, Yuki Saito, Wataru Nakata +1
This paper introduces CraBERT, a pre-trained phoneme encoder (PPEnc) designed for efficient pre-training in text-to-speech (TTS). CraBERT employs a cascade-fusion architecture and…
Speaker-Conditioned Phrase Break Prediction for Text-to-Speech with Phoneme-Level Pre-trained Language Model
Dong Yang, Yuki Saito, Takaaki Saeki +4
This paper advances phrase break prediction (also known as phrasing) in multi-speaker text-to-speech (TTS) systems. We integrate speaker-specific features by leveraging speaker emb…
Causal Speech Enhancement with Predicting Semantics based on Quantized Self-supervised Learning Features
Emiru Tsunoo, Yuki Saito, Wataru Nakata +1
Real-time speech enhancement (SE) is essential to online speech communication. Causal SE models use only the previous context while predicting future information, such as phoneme c…