1 citations · 2 across the 5 of their papers we have counts for
7 papers
Data-independent Beamforming for End-to-end Multichannel Multi-speaker ASR
Can Cui, Paul Magron, Mostafa Sadeghi +1
Automatic speech recognition (ASR) in multichannel, multi-speaker scenarios remains challenging due to ambient noise, reverberation and overlapping speakers. In this paper, we prop…
Speaker Embeddings to Improve Tracking of Intermittent and Moving Speakers
Taous Iatariene, Can Cui, Alexandre Guérin +1
Speaker tracking methods often rely on spatial observations to assign coherent track identities over time. This raises limits in scenarios with intermittent and moving speakers, i.…
Joint Beamforming and Speaker-Attributed ASR for Real Distant-Microphone Meeting Transcription
Can Cui, Imran Ahamad Sheikh, Mostafa Sadeghi +1
Distant-microphone meeting transcription is a challenging task. State-of-the-art end-to-end speaker-attributed automatic speech recognition (SA-ASR) architectures lack a multichann…
Improving Speaker Assignment in Speaker-Attributed ASR for Real Meeting Applications
Can Cui, Imran Ahamad Sheikh, Mostafa Sadeghi +1
Past studies on end-to-end meeting transcription have focused on model architecture and have mostly been evaluated on simulated meeting data. We present a novel study aiming to opt…
End-to-end Joint Punctuated and Normalized ASR with a Limited Amount of Punctuated Training Data
Can Cui, Imran Ahamad Sheikh, Mostafa Sadeghi +1
Joint punctuated and normalized automatic speech recognition (ASR) aims at outputing transcripts with and without punctuation and casing. This task remains challenging due to the l…
End-to-end Multichannel Speaker-Attributed ASR: Speaker Guided Decoder and Input Feature Analysis
Can Cui, Imran Ahamad Sheikh, Mostafa Sadeghi +1
We present an end-to-end multichannel speaker-attributed automatic speech recognition (MC-SA-ASR) system that combines a Conformer-based encoder with multi-frame crosschannel atten…
CAusal and collaborative proxy-tasKs lEarning for Semi-Supervised Domain Adaptation
Wenqiao Zhang, Changshuo Liu, Can Cui +1
Semi-supervised domain adaptation (SSDA) adapts a learner to a new domain by effectively utilizing source domain data and a few labeled target samples. It is a practical yet under-…