In speaker-adaptive HMM-based speech synthesis, there are a few speakers whose synthetic speech sounds worse than that of other speakers, despite having the same amount of adaptat...
Junichi Yamagishi, Oliver Watts, Simon King, Bela ...
Sparse Component Analysis is a relatively young technique that relies upon a representation of signal occupying only a small part of a larger space. Mixtures of sparse components ...
This paper proposes a technique for speaker and language adaptive training for HMM-based polyglot speech synthesis. Language-specific context-dependencies in the system are captur...
Interlocutors are known to mutually adapt during conversation. Recent studies have questioned the adaptation of phonological representations and kinematics of phonetic variables s...
We present a new method for speaker verification that uses the diversity of information from multiple feature representations. The principle behind the method is that certain feat...
This study revisits the face-to-tongue articulatory inversion problem in speech. We compare the Multi Linear Regression method (MLR) with two more sophisticated methods based on H...
The under-determined blind source separation (BSS) problem is usually solved using the sparse component analysis (SCA) technique. In SCA, the BSS is usually solved in two steps, w...
Pure frequency-based audio fingerprint systems have the capacity of handling very short fingerprints while being highly robust to perturbations such as additive noise or compressi...
A novel framework for background music identification is proposed in this paper. Given a piece of audio signals that mixes background music with speech/noise, we identify the musi...