Zobrazeno 1 - 10
of 97
pro vyhledávání: '"Larcher, Anthony"'
Biometric recognition systems are security systems based on intrinsic properties of their users, usually encoded in high dimension representations called embeddings, which potential theft would represent a greater threat than a temporary password or
Externí odkaz:
http://arxiv.org/abs/2408.08918
Publikováno v:
Speaker and Language Recognition Workshop - Odyssey, Jun 2024, Qu{\'e}bec (Canada), Canada
Speech resynthesis is a generic task for which we want to synthesize audio with another audio as input, which finds applications for media monitors and journalists.Among different tasks addressed by speech resynthesis, voice conversion preserves the
Externí odkaz:
http://arxiv.org/abs/2408.02712
Speaker Diarization (SD) aims at grouping speech segments that belong to the same speaker. This task is required in many speech-processing applications, such as rich meeting transcription. In this context, distant microphone arrays usually capture th
Externí odkaz:
http://arxiv.org/abs/2406.03251
Voice Activity Detection (VAD) and Overlapped Speech Detection (OSD) are key pre-processing tasks for speaker diarization. In the meeting context, it is often easier to capture speech with a distant device. This consideration however leads to severe
Externí odkaz:
http://arxiv.org/abs/2402.08312
Autor:
Lebourdais, Martin, Mariotte, Théo, Tahon, Marie, Larcher, Anthony, Laurent, Antoine, Montresor, Silvio, Meignier, Sylvain, Thomas, Jean-Hugh
Voice activity and overlapped speech detection (respectively VAD and OSD) are key pre-processing tasks for speaker diarization. The final segmentation performance highly relies on the robustness of these sub-tasks. Recent studies have shown VAD and O
Externí odkaz:
http://arxiv.org/abs/2307.13012
Speaker diarization is the task of answering Who spoke and when? in an audio stream. Pipeline systems rely on speech segmentation to extract speakers' segments and achieve robust speaker diarization. This paper proposes a common framework to solve th
Externí odkaz:
http://arxiv.org/abs/2306.04268
Publikováno v:
Proc. 2021 ISCA Symposium on Security and Privacy in Speech Communication (62-66)
Speech data carries a range of personal information, such as the speaker's identity and emotional state. These attributes can be used for malicious purposes. With the development of virtual assistants, a new generation of privacy threats has emerged.
Externí odkaz:
http://arxiv.org/abs/2305.01759
Publikováno v:
INTERSPEECH 2022 - Human and Humanizing Speech Technology, Sep 2022, incheon, South Korea
Speech signals contain a lot of sensitive information, such as the speaker's identity, which raises privacy concerns when speech data get collected. Speaker anonymization aims to transform a speech signal to remove the source speaker's identity while
Externí odkaz:
http://arxiv.org/abs/2208.10497
With the popularity of virtual assistants (e.g., Siri, Alexa), the use of speech recognition is now becoming more and more widespread.However, speech signals contain a lot of sensitive information, such as the speaker's identity, which raises privacy
Externí odkaz:
http://arxiv.org/abs/2203.09518
Publikováno v:
ASRU 2021 - IEEE Automatic Speech Recognition and Understanding Workshop, Dec 2021, Cartagena, Colombia
This paper explores various attack scenarios on a voice anonymization system using embeddings alignment techniques. We use Wasserstein-Procrustes (an algorithm initially designed for unsupervised translation) or Procrustes analysis to match two sets
Externí odkaz:
http://arxiv.org/abs/2110.05431