183 citations · 507 across the 18 of their papers we have counts for
10 papers · 1 filter
Privacy-Preserving Adversarial Representation Learning in ASR: Reality or Illusion?
Brij Mohan Lal Srivastava, Aurélien Bellet, Marc Tommasi +1
Automatic speech recognition (ASR) is a key technology in many services and applications. This typically requires user devices to send their speech data to the cloud for ASR decodi…
The Speed Submission to DIHARD II: Contributions & Lessons Learned
Md Sahidullah, Jose Patino, Samuele Cornell +11
This paper describes the speaker diarization systems developed for the Second DIHARD Speech Diarization Challenge (DIHARD II) by the Speed team. Besides describing the system, whic…
Joint NN-Supported Multichannel Reduction of Acoustic Echo, Reverberation and Noise
Guillaume Carbajal, Romain Serizel, Emmanuel Vincent +1
We consider the problem of simultaneous reduction of acoustic echo, reverberation and noise. In real scenarios, these distortion sources may occur simultaneously and reducing them…
Evaluating Voice Conversion-based Privacy Protection against Informed Attackers
Brij Mohan Lal Srivastava, Nathalie Vauquier, Md Sahidullah +3
Speech data conveys sensitive speaker attributes like identity or accent. With a small amount of found data, such attributes can be inferred and exploited for malicious purposes: v…
SLOGD: Speaker LOcation Guided Deflation approach to speech separation
Sunit Sivasankaran, Emmanuel Vincent, Dominique Fohr
Speech separation is the process of separating multiple speakers from an audio recording. In this work we propose to separate the sources using a Speaker LOcalization Guided Deflat…
Lead2Gold: Towards exploiting the full potential of noisy transcriptions for speech recognition
Adrien Dufraux, Emmanuel Vincent, Awni Hannun +2
The transcriptions used to train an Automatic Speech Recognition (ASR) system may contain errors. Usually, either a quality control stage discards transcriptions with too many erro…