5 papers · 1 filter
Personalized Speech Enhancement Without a Separate Speaker Embedding Model
Tanel Pärnamaa, Ando Saabas
Personalized speech enhancement (PSE) models can improve the audio quality of teleconferencing systems by adapting to the characteristics of a speaker's voice. However, most existi…
The ICASSP 2024 Audio Deep Packet Loss Concealment Challenge
Lorenz Diener, Solomiya Branets, Ando Saabas +1
Audio packet loss concealment is the hiding of gaps in VoIP audio streams caused by network packet loss. With the ICASSP 2024 Audio Deep Packet Loss Concealment Grand Challenge, we…
ICASSP 2024 Speech Signal Improvement Challenge
Nicolae Catalin Ristea, Ando Saabas, Ross Cutler +3
The ICASSP 2024 Speech Signal Improvement Grand Challenge is intended to stimulate research in the area of improving the speech signal quality in communication systems. This marks…
DeepVQE: Real Time Deep Voice Quality Enhancement for Joint Acoustic Echo Cancellation, Noise Suppression and Dereverberation
Evgenii Indenbom, Nicolae-Catalin Ristea, Ando Saabas +3
Acoustic echo cancellation (AEC), noise suppression (NS) and dereverberation (DR) are an integral part of modern full-duplex communication systems. As the demand for teleconferenci…
PLCMOS -- a data-driven non-intrusive metric for the evaluation of packet loss concealment algorithms
Lorenz Diener, Marju Purin, Sten Sootla +3
Speech quality assessment is a problem for every researcher working on models that produce or process speech. Human subjective ratings, the gold standard in speech quality assessme…