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Leveraging Timestamp Information for Serialized Joint Streaming Recognition and Translation
Sara Papi, Peidong Wang, Junkun Chen +4
The growing need for instant spoken language transcription and translation is driven by increased global communication and cross-lingual interactions. This has made offering transl…
t-SOT FNT: Streaming Multi-talker ASR with Text-only Domain Adaptation Capability
Jian Wu, Naoyuki Kanda, Takuya Yoshioka +3
Token-level serialized output training (t-SOT) was recently proposed to address the challenge of streaming multi-talker automatic speech recognition (ASR). T-SOT effectively handle…
Profile-Error-Tolerant Target-Speaker Voice Activity Detection
Dongmei Wang, Xiong Xiao, Naoyuki Kanda +3
Target-Speaker Voice Activity Detection (TS-VAD) utilizes a set of speaker profiles alongside an input audio signal to perform speaker diarization. While its superiority over conve…
DiariST: Streaming Speech Translation with Speaker Diarization
Mu Yang, Naoyuki Kanda, Xiaofei Wang +5
End-to-end speech translation (ST) for conversation recordings involves several under-explored challenges such as speaker diarization (SD) without accurate word time stamps and han…
SpeechX: Neural Codec Language Model as a Versatile Speech Transformer
Xiaofei Wang, Manthan Thakker, Zhuo Chen +7
Recent advancements in generative speech models based on audio-text prompts have enabled remarkable innovations like high-quality zero-shot text-to-speech. However, existing models…
Adapting Multi-Lingual ASR Models for Handling Multiple Talkers
Chenda Li, Yao Qian, Zhuo Chen +5
State-of-the-art large-scale universal speech models (USMs) show a decent automatic speech recognition (ASR) performance across multiple domains and languages. However, it remains…
i-Code V2: An Autoregressive Generation Framework over Vision, Language, and Speech Data
Ziyi Yang, Mahmoud Khademi, Yichong Xu +16
The convergence of text, visual, and audio data is a key step towards human-like artificial intelligence, however the current Vision-Language-Speech landscape is dominated by encod…
Factual Consistency Oriented Speech Recognition
Naoyuki Kanda, Takuya Yoshioka, Yang Liu
This paper presents a novel optimization framework for automatic speech recognition (ASR) with the aim of reducing hallucinations produced by an ASR model. The proposed framework o…