4 papers
All-in-One ASR: Unifying Encoder-Decoder Models of CTC, Attention, and Transducer in Dual-Mode ASR
Takafumi Moriya, Masato Mimura, Tomohiro Tanaka +3
This paper proposes a unified framework, All-in-One ASR, that allows a single model to support multiple automatic speech recognition (ASR) paradigms, including connectionist tempor…
Generic Speech Enhancement with Self-Supervised Representation Space Loss
Hiroshi Sato, Tsubasa Ochiai, Marc Delcroix +3
Single-channel speech enhancement is utilized in various tasks to mitigate the effect of interfering signals. Conventionally, to ensure the speech enhancement performs optimally, t…
Alignment-Free Training for Transducer-based Multi-Talker ASR
Takafumi Moriya, Shota Horiguchi, Marc Delcroix +5
Extending the RNN Transducer (RNNT) to recognize multi-talker speech is essential for wider automatic speech recognition (ASR) applications. Multi-talker RNNT (MT-RNNT) aims to ach…
Factor-Conditioned Speaking-Style Captioning
Atsushi Ando, Takafumi Moriya, Shota Horiguchi +1
This paper presents a novel speaking-style captioning method that generates diverse descriptions while accurately predicting speaking-style information. Conventional learning crite…