7 accepted papers
This study explores various speech data augmentation methods for the task of noise-robust fundamental frequency (F0) estimation with neural networks. The explored augmentation strategies are split into additive noise and channel-based augmentation and into vocoder-based augmentation methods. In voco…
This paper proposes a method for generating speech from filterbank mel frequency cepstral coefficients (MFCC), which are widely used in speech applications, such as ASR, but are generally considered unusable for speech synthesis. First, we predict fundamental frequency and voicing information from M…
Auto-regressive modeling is a prevalent source-filter separation method of speech. Conventional linear prediction (LP) and its derivatives such as weighted linear prediction (WeLP) produce parametric spectral models within a linear frequency scale, whereas frequency-warped linear prediction (WaLP) c…
In statistical parametric speech synthesis (SPSS), a few studies have investigated the Lombard effect, specifically by using hidden Markov model (HMM)-based systems. Recently, artificial neural networks have demonstrated promising results in SPSS, specifically by using long short-term memory recurre…
Achieving high quality and naturalness in statistical parametric synthesis of female voices remains to be difficult despite recent advances in the study area. Vocoding is one such key element in all statistical speech synthesizers that is known to affect the synthesis quality and naturalness. The pr…
Recent research on temporally weighted linear prediction shows that quasi closed phase (QCP) analysis of speech signals provides better modeling of the vocal tract and the glottal source. Quasi closed phase analysis gives more weightage on the closed phase of the glottal cycle, at the same time deem…
In the analysis of speech production, information about the voice source can be obtained non-invasively with glottal inverse filtering (GIF) methods. Current state-of-the-art GIF methods are capable of producing high-quality estimates in suitable conditions (e.g. low noise and reverberation), but th…