• Publications
  • Influence
Continuous probabilistic transform for voice conversion
TLDR
The design of a new methodology for representing the relationship between two sets of spectral envelopes and the proposed transform greatly improves the quality and naturalness of the converted speech signals compared with previous proposed conversion methods.
Applying the harmonic plus noise model in concatenative speech synthesis
  • Y. Stylianou
  • Computer Science
    IEEE Trans. Speech Audio Process.
  • 2001
TLDR
The harmonic plus noise model (HNM) for concatenative text-to-speech (TTS) synthesis provides high-quality speech synthesis while outperforming other models for synthesis (e.g., TD-PSOLA) in intelligibility, naturalness, and pleasantness.
Bird detection in audio: A survey and a challenge
TLDR
New datasets and an IEEE research challenge are introduced to make possible the development of fully automatic algorithms for bird sound detection, and identify a widespread need for tuning-free and species-agnostic approaches.
Speech-in-noise intelligibility improvement based on spectral shaping and dynamic range compression
TLDR
Experiments with speech shaped (SSN) and competing speaker types of noise at various low SNR values show that the suggested approach outperforms state-of-the art methods in terms of the Speech Intelligibility Index (SII).
Voice Pathology Detection and Discrimination Based on Modulation Spectral Features
  • M. Markaki, Y. Stylianou
  • Mathematics, Computer Science
    IEEE Transactions on Audio, Speech, and Language…
  • 1 September 2011
TLDR
The information provided by a joint acoustic and modulation frequency representation, referred to as modulation spectrum, for detection and discrimination of voice disorders is explored and the suggested approach significantly outperformed the performance of cepstral-based features.
The AT & T NEXT-GEN TTS system
The new AT&T TTS system for general U.S. English text is based on best‐choice components picked from the AT&T Flextalk TTS, the Festival System from the University of Edinburgh, and ATR’s CHATR
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