2 citations · 3 across the 4 of their papers we have counts for
4 papers
On-Device Speaker Anonymization of Acoustic Embeddings for ASR based onFlexible Location Gradient Reversal Layer
Md Asif Jalal, Pablo Peso Parada, Jisi Zhang +5
Smart devices serviced by large-scale AI models necessitates user data transfer to the cloud for inference. For speech applications, this means transferring private user informatio…
Online Continual Learning in Keyword Spotting for Low-Resource Devices via Pooling High-Order Temporal Statistics
Umberto Michieli, Pablo Peso Parada, Mete Ozay
Keyword Spotting (KWS) models on embedded devices should adapt fast to new user-defined words without forgetting previous ones. Embedded devices have limited storage and computatio…
pMCT: Patched Multi-Condition Training for Robust Speech Recognition
Pablo Peso Parada, Agnieszka Dobrowolska, Karthikeyan Saravanan +1
We propose a novel Patched Multi-Condition Training (pMCT) method for robust Automatic Speech Recognition (ASR). pMCT employs Multi-condition Audio Modification and Patching (MAMP)…
Evaluating the Non-Intrusive Room Acoustics Algorithm with the ACE Challenge
Pablo Peso Parada, Dushyant Sharma, Toon van Waterschoot +1
We present a single channel data driven method for non-intrusive estimation of full-band reverberation time and full-band direct-to-reverberant ratio. The method extracts a number…