12 accepted papers
Classification of normal vs. pathological infant cry is an interesting and technologically challenging research problem due to quasi-periodic sampling of vocal tract spectrum by high pitch-source harmonics resulting in extremely poor spectral resolution for commonly used spectral features, such as M…
Voice assistants (VAs) are highly vulnerable to replay attacks, where the impostor plays pre-recorded voice samples to gain an unauthorized access to personalised devices. To that effect, we present an optimal microphone-channel selection scheme using Cross-Teager Energy Operator (CTEO) for spoofed…
In this paper, we present a multi-domain speech conversion technique by proposing a Multi-domain Speech Conversion Network (MSpeC-Net) architecture for solving the less-explored area of Non-Audible Murmur-to-SPeeCH (NAM2-SPCH) conversion. The murmur produced by the speaker and captured by the NAM mi…
The Automatic Speaker Verification (ASV) systems are vulnerable to spoofing attacks. Detecting replay attack is the challenging Spoof Speech Detection (SSD) task, as several factors are involved during replay mechanism. Hence, it is important to analyze these factors for effective SSD task. This pap…
Obtaining aligned spectral pairs in case of non-parallel data for stand-alone Voice Conversion (VC) technique is a challenging research problem. Unsupervised alignment algorithm, namely, an Iterative combination of a Nearest Neighbor search step and a Conversion step Alignment (INCA) iteratively tri…
The success of time-frequency (T-F) mask-based approaches is dependent on the accuracy of predicted mask given the noisy spectral features. The state-of-the-art methods in T- F masking-based enhancement employ Deep Neural Network (DNN) to predict mask. Recently, Generative Adversarial Networks (GAN)…
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 propos…
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 toward…
Text-to-speech (TTS) synthesis systems are being advanced to achieve naturalness and intelligibility in synthetic speech. Unit selection-based synthesis (USS) and Hidden Markov Model-based text-to-speech synthesis systems (HTS) are recent techniques in this area. USS-based synthetic speech is known…
Current countermeasures used in spoof detectors (for speech synthesis (SS) and voice conversion (VC)) are generally phase-based (as vocoders in SS and VC systems lack phase-information). These approaches may possibly fail for non-vocoder or unit-selection-based spoofs. In this work, we explore excit…
Convolutional Restricted Boltzmann Machine (ConvRBM) as a model for speech signal is presented in this paper. We have developed ConvRBM with sampling from noisy rectified linear units (NReLUs). ConvRBM is trained in an unsupervised way to model speech signal of arbitrary lengths. Weights of the mode…
In this paper, we propose a novel algorithm which uses simple lowpass filtering as pre-processing for detection of epochs. Lowpass filtering with an appropriate cut-off frequency removes the effect of vocal tract characteristics as formants lie in relatively higher frequency regions. The method is e…