Voice Conversion (VC) converts the speaking style of a source speaker to the speaking style
of a target speaker by preserving the linguistic content of a given speech utterance …

Alignment is a key step before learning a mapping function between a source and a target
speaker's spectral features in various state-of-the-art parallel data Voice Conversion (VC) …

In the absence of vocal fold vibrations, movement of articulators which produced the
respiratory sound can be captured by the soft tissue of the head using the nonaudible …

Abstract Non-parallel Voice Conversion (VC) has gained significant attention since last one
decade. Obtaining corresponding speech frames from both the source and target speakers …

Voice Conversion (VC) requires an alignment of the spectral features before learning the
mapping function, due to the speaking rate variations across the source and target speakers …

Development of text-independent Voice Conversion (VC) has gained more research interest
for last one decade. Alignment of the source and target speakers' spectral features before …

Obtaining aligned spectral pairs in case of non-parallel data for stand-alone Voice
Conversion (VC) technique is a challenging research problem. Unsupervised alignment …

Nearest Neighbor (NN)-based alignment techniques are popular in non-parallel Voice
Conversion (VC). The performance of NN-based alignment improves with the information …

Based on a survey in 2020, out of the total number of people using the internet, the
percentage of users who watch video content on any device is on average 85-90%. Out of …

Understanding how a particular speaker is producing speech, and mimicking one's voice is
a difficult research problem due to the sophisticated mechanism involved in speech …