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In Frequency Warping (FW)-based Voice Conversion (VC), the source spectrum is modified to match the frequency-axis of the target spectrum followed by an Amplitude Scaling (AS) to compensate the amplitude differences between the warped spectrum and the actual target spectrum. In this paper, we propose a novel AS technique which linearly transfers the amplitude of the frequency-warped spectrum using...
We propose a novel application of the acoustic-to-articulatory inversion (AAI) towards a quality assessment of the voice converted speech. The ability of humans to speak effortlessly requires the coordinated movements of various articulators, muscles, etc. This effortless movement contributes towards a naturalness, intelligibility and speaker's identity (which is partially present in voice converted...
We propose to use multiscale fractal dimension (FD)-based features for phoneme classification task at frame-level. During speech production, turbulence is created and hence vortices (generated due to presence of separated airflow) may travel along the vocal tract and excite vocal tract resonators. This turbulence and in effect, the embedded features of different phoneme classes, can be captured by...
The generalized statistical framework of Hidden Markov Model (HMM) has been successfully applied from the field of speech recognition to speech synthesis. In this paper, we have applied HMM-based Speech Synthesis (HTS) method to Gujarati (one of the official languages of India). Adaption and evaluation of HTS for Gujarati language has been done here. In addition, to understand the influence of asymmetrical...
The generalized statistical framework of Hidden Markov Model (HMM) has been successfully applied from the field of speech recognition to speech synthesis. In this work, we have applied HMM-based Speech Synthesis System (HTS) method to Gujarati language. Adaption and evaluation of HTS for Gujarati language has been done here. Evaluation of HTS system built using Gujarati data is done in terms of naturalness...
We propose to use multiscale fractal dimension (MFD) as components of feature vectors for automatic speech recognition (ASR) especially in low resource languages. Speech, which is known to be a nonlinear process, can be efficiently represented by extracting some nonlinear properties, such as fractal dimension, from the speech segment. During speech production, vortices (generated due to presence of...
In this paper, use of Viterbi-based algorithm and spectral transition measure (STM)-based algorithm for the task of speech data labeling is being attempted. In the STM framework, we propose use of several spectral features such as recently proposed cochlear filter cepstral coefficients (CFCC), perceptual linear prediction cepstral coefficients (PLPCC) and RelAtive SpecTrAl (RASTA)-based PLPCC in addition...
In this paper, we discuss a consortium effort on building text to speech (TTS) systems for 13 Indian languages. There are about 1652 Indian languages. A unified framework is therefore attempted required for building TTSes for Indian languages. As Indian languages are syllable-timed, a syllable-based framework is developed. As quality of speech synthesis is of paramount interest, unit-selection synthesizers...
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