From the 1 of 8 linked papers with an AI index.
1 citations · 1 across the 4 of their papers we have counts for
8 papers
Audio Diarization: A New Paradigm for Exploring Audio Recordings with Unknown Event Classes
Alexander Werning, Reinhold Haeb-Umbach
The paper introduces audio diarization, a task that locates the start and end times of sound events (including overlapping ones) without prior knowledge of event classes, and shows…
Speech Quality Embeddings for Improved Detection and Classification of Degradations in Speech Signals
Michael Kuhlmann, Tobias Cord-Landwehr, Reinhold Haeb-Umbach
Automatic subjective speech quality assessment (SSQA) traditionally estimates speech quality on an utterance or system level. While this resolution was adequate for older transmiss…
Disentangling Pitch and Creak for Speaker Identity Preservation in Speech Synthesis
Frederik Rautenberg, Jana Wiechmann, Petra Wagner +1
We introduce a system capable of faithfully modifying the perceptual voice quality of creak while preserving the speaker's perceived identity. While it is well known that high crea…
Speech Quality-Based Localization of Low-Quality Speech and Text-to-Speech Synthesis Artefacts
Michael Kuhlmann, Alexander Werning, Thilo von Neumann +1
A large number of works view the automatic assessment of speech from an utterance- or system-level perspective. While such approaches are good in judging overall quality, they cann…
Synthesizing speech with selected perceptual voice qualities - A case study with creaky voice
Frederik Rautenberg, Fritz Seebauer, Jana Wiechmann +3
The control of perceptual voice qualities in a text-to-speech (TTS) system is of interest for applications where unmanipu- lated and manipulated speech probes can serve to illustra…
Towards Frame-level Quality Predictions of Synthetic Speech
Michael Kuhlmann, Fritz Seebauer, Petra Wagner +1
While automatic subjective speech quality assessment has witnessed much progress, an open question is whether an automatic quality assessment at frame resolution is possible. This…