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Found 7 papers, 1 papers with code
MicroT: Low-Energy and Adaptive Models for MCUs
On MCUs, compared to the standard full model inference, MicroT can save up to about 29. 13% in energy consumption.
A study on the impact of Self-Supervised Learning on automatic dysarthric speech assessment
We are the first to evaluate the representations from pre-trained state-of-the-art Self-Supervised models across three downstream tasks on dysarthric speech: disease classification, word recognition and intelligibility classification, and under three noise scenarios on the UA-Speech dataset.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Evaluating The Robustness of Self-Supervised Representations to Background/Foreground Removal
Despite impressive empirical advances of SSL in solving various tasks, the problem of understanding and characterizing SSL representations learned from input data remains relatively under-explored.
Configurable Privacy-Preserving Automatic Speech Recognition
We show that overlapping speech inputs to ASR systems present further privacy concerns, and how these may be mitigated using speech separation and optimization techniques.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+3
Paralinguistic Privacy Protection at the Edge
One approach to mitigate the risk of paralinguistic-based privacy breaches is to exploit a combination of cloud-based processing with privacy-preserving, on-device paralinguistic information learning and filtering before transmitting voice data.
Privacy-preserving Voice Analysis via Disentangled Representations
Our experimental evaluation over five datasets shows that the proposed framework can effectively defend against attribute inference attacks by reducing their success rates to approximately that of guessing at random, while maintaining accuracy in excess of 99% for the tasks of interest.
Emotionless: Privacy-Preserving Speech Analysis for Voice Assistants
The voice signal is a rich resource that discloses several possible states of a speaker, such as emotional state, confidence and stress levels, physical condition, age, gender, and personal traits.
