6 accepted papers
Phase gradients can help enforce phase consistency across time and frequency, further improving the output of speech enhancement approaches. Recently, neural networks were used to estimate the phase gradients from the short-term amplitude spectra of clean speech. These were then used to synthesise p…
Weak harmonics of voiced speech segments are often lost during the process of noise suppression – especially at low SNRs. This leads to a distortion in the harmonic structure, and an accompanying loss in quality. In this paper, inspired by previous work on speech harmonic enhancement using statistic…
For separating sources captured by ad hoc distributed microphones a key first step is assigning the microphones to the appropriate source-dominated clusters. The features used for such (blind) clustering are based on a fixed length embedding of the audio signals in a high-dimensional latent space. I…
Even without a separate tracking algorithm, the directions of arrival (DOAs) of moving talkers can be estimated with a deep neural network (DNN) when the movement trajectories used for training allow the generalization to real signals. Previously, we proposed a framework for generating training data…
This paper is concerned with the task of speaker verification on audio with multiple overlapping speakers. Most speaker verification systems are designed with the assumption of a single speaker being present in a given audio segment. However, in a real-world setting this assumption does not always h…
The weighted least-squares (WLS) direction-of-arrival estimator that minimizes an error based on interchannel phase differences is both computationally simple and flexible. However, the approach has several limitations, including an inability to cope with spatial aliasing and a sensitivity to phase…