4 papers
When Intent Arrives Late: A Benchmark for Full-Duplex Speech Models under Delayed Intent Revelation
Yang Xiao, Tianyi Peng, Hanyu Meng +1
Native full-duplex speech models can respond before a user finishes speaking, making the behavior of the model depend on both the final utterance and when intent-defining informati…
AdaKWS: Towards Robust Keyword Spotting with Test-Time Adaptation
Yang Xiao, Tianyi Peng, Yanghao Zhou +1
Spoken keyword spotting (KWS) aims to identify keywords in audio for wide applications, especially on edge devices. Current small-footprint KWS systems focus on efficient model des…
AnalyticKWS: Towards Exemplar-Free Analytic Class Incremental Learning for Small-footprint Keyword Spotting
Yang Xiao, Tianyi Peng, Rohan Kumar Das +2
Keyword spotting (KWS) offers a vital mechanism to identify spoken commands in voice-enabled systems, where user demands often shift, requiring models to learn new keywords continu…
Dark Experience for Incremental Keyword Spotting
Tianyi Peng, Yang Xiao
Spoken keyword spotting (KWS) is crucial for identifying keywords within audio inputs and is widely used in applications like Apple Siri and Google Home, particularly on edge devic…