A reminder for tomorrow's seminar by Hari Parthasarathi.
---------- Forwarded message ----------
From: Guillaume Desjardins <guillaume.desjardins(a)gmail.com>
Date: Mon, May 9, 2011 at 1:50 PM
Subject: UdeM-McGill-MITACS machine learning seminar Wed May 11th @
14h00, AA3195
To: lisa_seminaires(a)mercure.iro.umontreal.ca
A UdeM-McGill-MITACS machine learning seminar will be held this
Wesdnesday, May 11th. The talk given by Hari Parthasarathi, will take
place from 14h00-15h00 in the room AA3195 (pavillon Andre-Aisenstadt)
at the Université de Montréal. Hope to see you there !
Title: Wordless sounds aka privacy-sensitive audio
Speaker: Hari Parthasarathi
Abstract: In this talk, I will discuss a key issue in the ubiquitous
capture and analysis of audio, namely, ``privacy''. Some studies suggest
that the linguistic message in audio is perhaps the most
privacy-sensitive information. Towards this, we have proposed and
analyzed robust, audio features having low linguistic information for 2
specific tasks: (a) speech/nonspeech detection - SND (b) speaker
diarization.
For the SND task, in addition to reinterpreting classical features in a
privacy-sensitive framework, we quantify the abstract notion of privacy.
Furthermore, the robustness of these features (matched vs mismatched
conditions, near-field vs far-field microphones) is studied in a large
dataset of nearly 500 hours.
For the diarization task, besides investigating linear prediction
residual, we derive features based on deep neural networks. We
benchmark these approaches against the MFCC features in single and
multiple distant microphone scenarios. We performed human and automatic
speech recognition tests to assess privacy.
