Evaluation of glottal closure instant detection in a range of voice qualities
Speech Communication
Synthesis and perception of breathy, normal, and Lombard speech in the presence of noise
Computer Speech and Language
Quasi Closed Phase Glottal Inverse Filtering Analysis With Weighted Linear Prediction
IEEE/ACM Transactions on Audio, Speech and Language Processing (TASLP)
Phonetic feature extraction for context-sensitive glottal source processing
Speech Communication
Pitch-Scaled Spectrum Based Excitation Model for HMM-based Speech Synthesis
Journal of Signal Processing Systems
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This paper describes an hidden Markov model (HMM)-based speech synthesizer that utilizes glottal inverse filtering for generating natural sounding synthetic speech. In the proposed method, speech is first decomposed into the glottal source signal and the model of the vocal tract filter through glottal inverse filtering, and thus parametrized into excitation and spectral features. The source and filter features are modeled individually in the framework of HMM and generated in the synthesis stage according to the text input. The glottal excitation is synthesized through interpolating and concatenating natural glottal flow pulses, and the excitation signal is further modified according to the spectrum of the desired voice source characteristics. Speech is synthesized by filtering the reconstructed source signal with the vocal tract filter. Experiments show that the proposed system is capable of generating natural sounding speech, and the quality is clearly better compared to two HMM-based speech synthesis systems based on widely used vocoder techniques.