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Personalizing Keyword Spotting with Speaker Information
Keyword spotting systems often struggle to generalize to a diverse population with various accents and age groups.
Locale Encoding For Scalable Multilingual Keyword Spotting Models
A Multilingual Keyword Spotting (KWS) system detects spokenkeywords over multiple locales.
A Conformer-based Waveform-domain Neural Acoustic Echo Canceller Optimized for ASR Accuracy
Acoustic Echo Cancellation (AEC) is essential for accurate recognition of queries spoken to a smart speaker that is playing out audio.
Production federated keyword spotting via distillation, filtering, and joint federated-centralized training
We trained a keyword spotting model using federated learning on real user devices and observed significant improvements when the model was deployed for inference on phones.
A Conformer-based ASR Frontend for Joint Acoustic Echo Cancellation, Speech Enhancement and Speech Separation
Compared to the noisy baseline, the joint model reduces the word error rate in low signal-to-noise ratio conditions by at least 71% on our echo cancellation dataset, 10% on our noisy dataset, and 26% on our multi-speaker dataset.
A Neural Acoustic Echo Canceller Optimized Using An Automatic Speech Recognizer And Large Scale Synthetic Data
We consider the problem of recognizing speech utterances spoken to a device which is generating a known sound waveform; for example, recognizing queries issued to a digital assistant which is generating responses to previous user inputs.
