most citedAnonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy

3 citations · 8 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CL2023

The IMS Toucan System for the Blizzard Challenge 2023

Florian Lux, Julia Koch, Sarina Meyer +5

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 proces…

cs.CL2022★ 2 cited

Low-Resource Multilingual and Zero-Shot Multispeaker TTS

Florian Lux, Julia Koch, Ngoc Thang Vu

While neural methods for text-to-speech (TTS) have shown great advances in modeling multiple speakers, even in zero-shot settings, the amount of data needed for those approaches is…

cs.SD2022★ 3 cited

Anonymizing Speech with Generative Adversarial Networks to Preserve Speaker Privacy

Sarina Meyer, Pascal Tilli, Pavel Denisov +3

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 wit…

cs.SD2022★ 1 cited

Speaker Anonymization with Phonetic Intermediate Representations

Sarina Meyer, Florian Lux, Pavel Denisov +3

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…

eess.AS2022★ 2 cited

PoeticTTS -- Controllable Poetry Reading for Literary Studies

Julia Koch, Florian Lux, Nadja Schauffler +6

Speech synthesis for poetry is challenging due to specific intonation patterns inherent to poetic speech. In this work, we propose an approach to synthesise poems with almost human…

cs.SD2022

Exact Prosody Cloning in Zero-Shot Multispeaker Text-to-Speech

Florian Lux, Julia Koch, Ngoc Thang Vu

The cloning of a speaker's voice using an untranscribed reference sample is one of the great advances of modern neural text-to-speech (TTS) methods. Approaches for mimicking the pr…