13 citations · 35 across the 14 of their papers we have counts for
14 papers
Prompting Large Language Models with Speech Recognition Abilities
Yassir Fathullah, Chunyang Wu, Egor Lakomkin +9
Large language models have proven themselves highly flexible, able to solve a wide range of generative tasks, such as abstractive summarization and open-ended question answering. I…
Towards Selection of Text-to-speech Data to Augment ASR Training
Shuo Liu, Leda Sarı, Chunyang Wu +4
This paper presents a method for selecting appropriate synthetic speech samples from a given large text-to-speech (TTS) dataset as supplementary training data for an automatic spee…
Multi-Head State Space Model for Speech Recognition
Yassir Fathullah, Chunyang Wu, Yuan Shangguan +8
State space models (SSMs) have recently shown promising results on small-scale sequence and language modelling tasks, rivalling and outperforming many attention-based approaches. I…
Anchored Speech Recognition with Neural Transducers
Desh Raj, Junteng Jia, Jay Mahadeokar +4
Neural transducers have achieved human level performance on standard speech recognition benchmarks. However, their performance significantly degrades in the presence of cross-talk,…
Streaming Transformer Transducer Based Speech Recognition Using Non-Causal Convolution
Yangyang Shi, Chunyang Wu, Dilin Wang +9
This paper improves the streaming transformer transducer for speech recognition by using non-causal convolution. Many works apply the causal convolution to improve streaming transf…
Flexi-Transducer: Optimizing Latency, Accuracy and Compute forMulti-Domain On-Device Scenarios
Jay Mahadeokar, Yangyang Shi, Yuan Shangguan +7
Often, the storage and computational constraints of embeddeddevices demand that a single on-device ASR model serve multiple use-cases / domains. In this paper, we propose aFlexible…