Speech tokenization is the task of representing speech signals as a sequence of discrete
units. Such representations can be later used for various downstream tasks including …

As many acoustic signal processing methods, for example for source separation or noise
canceling, operate in the magnitude spectrogram domain, the problem of reconstructing a …

Designing Audio Effect Plugins in C++ presents everything you need to know about digital
signal processing in an accessible way. Not just another theory-heavy digital signal …

Generative Spoken Language Modeling research focuses on optimizing speech Language
Models (LMs) using raw audio recordings without accessing any textual supervision. Such …

In this paper a frequency-domain pitch shifting approach based on the CQT is proposed.
The CQT is specifically attractive for pitch shifting because it can be implemented by …

While listening to spoken content, it is often desired to vary the speech rate while preserving
the speaker's timbre and pitch. To date, advanced signal processing techniques are used to …

Pitch-shifting is a process where the original pitch of the sound is increased or decreased
without affecting the length of the sound clip being recorded. Pitch shifters are being …

In this paper we present an original method mixing temporal and spectral processing to
reduce the phasiness in the phase vocoder. Phasiness is an inherent artifact of the phase …

This paper presents a low latency pitch shifting algorithm based on the Short-Time Fourier
Transform (STFT). Unlike existing STFT-based implementations of pitch shifting, the …

Adaptive time-scale modification (ATSM) adaptively adjusts audio speed and improves upon
previous systems by tailoring the scale for each phoneme in two steps: phoneme positioning …