Zobrazeno 1 - 10
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pro vyhledávání: '"Meyer, Sarina"'
Publikováno v:
Proc. Interspeech 2024, pp. 4448-4452
In speaker anonymization, speech recordings are modified in a way that the identity of the speaker remains hidden. While this technology could help to protect the privacy of individuals around the globe, current research restricts this by focusing al
Externí odkaz:
http://arxiv.org/abs/2407.02937
Autor:
Lux, Florian, Meyer, Sarina, Behringer, Lyonel, Zalkow, Frank, Do, Phat, Coler, Matt, Habets, Emanuël A. P., Vu, Ngoc Thang
In this work, we take on the challenging task of building a single text-to-speech synthesis system that is capable of generating speech in over 7000 languages, many of which lack sufficient data for traditional TTS development. By leveraging a novel
Externí odkaz:
http://arxiv.org/abs/2406.06403
Autor:
Tomashenko, Natalia, Miao, Xiaoxiao, Champion, Pierre, Meyer, Sarina, Wang, Xin, Vincent, Emmanuel, Panariello, Michele, Evans, Nicholas, Yamagishi, Junichi, Todisco, Massimiliano
The task of the challenge is to develop a voice anonymization system for speech data which conceals the speaker's voice identity while protecting linguistic content and emotional states. The organizers provide development and evaluation datasets and
Externí odkaz:
http://arxiv.org/abs/2404.02677
Customizing voice and speaking style in a speech synthesis system with intuitive and fine-grained controls is challenging, given that little data with appropriate labels is available. Furthermore, editing an existing human's voice also comes with eth
Externí odkaz:
http://arxiv.org/abs/2310.17502
Autor:
Lux, Florian, Koch, Julia, Meyer, Sarina, Bott, Thomas, Schauffler, Nadja, Denisov, Pavel, Schweitzer, Antje, Vu, Ngoc Thang
For our contribution to the Blizzard Challenge 2023, we improved on the system we submitted to the Blizzard Challenge 2021. Our approach entails a rule-based text-to-phoneme processing system that includes rule-based disambiguation of homographs in t
Externí odkaz:
http://arxiv.org/abs/2310.17499
Speaker anonymization is the task of modifying a speech recording such that the original speaker cannot be identified anymore. Since the first Voice Privacy Challenge in 2020, along with the release of a framework, the popularity of this research top
Externí odkaz:
http://arxiv.org/abs/2309.08049
We present our latest findings on backchannel modeling novelly motivated by the canonical use of the minimal responses Yeah and Uh-huh in English and their correspondent tokens in German, and the effect of encoding the speaker-listener interaction. B
Externí odkaz:
http://arxiv.org/abs/2304.04472
In order to protect the privacy of speech data, speaker anonymization aims for hiding the identity of a speaker by changing the voice in speech recordings. This typically comes with a privacy-utility trade-off between protection of individuals and us
Externí odkaz:
http://arxiv.org/abs/2210.07002
In this work, we propose a speaker anonymization pipeline that leverages high quality automatic speech recognition and synthesis systems to generate speech conditioned on phonetic transcriptions and anonymized speaker embeddings. Using phones as the
Externí odkaz:
http://arxiv.org/abs/2207.04834
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