Phonetic Subspace Features for Improved Query by Example Spoken Term Detection
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Model-based approaches to Speaker Verification (SV), such as Joint Factor Analysis (JFA), i-vector and relevance Maximum-a-Posteriori (MAP), have shown to provide state-of-the-art performance for text-dependent systems with fixed phrases. The performance o ...
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This thesis deals with exploiting the low-dimensional multi-subspace structure of speech towards the goal of improving acoustic modeling for automatic speech recognition (ASR). Leveraging the parsimonious hierarchical nature of speech, we hypothesize that ...
This paper focuses on the problem of query by example spoken term detection (QbE-STD) in zero-resource scenario. Current state-of-the-art approaches to tackle this problem rely on dynamic programming based template matching techniques using phone posterior ...
In hidden Markov model (HMM) based automatic speech recognition (ASR) system, modeling the statistical relationship between the acoustic speech signal and the HMM states that represent linguistically motivated subword units such as phonemes is a crucial st ...
Speech is a complex signal produced by a highly constrained articulation machinery. Neuro and psycholinguistic theories assert that speech can be decomposed into molecules of structured atoms. Although characterization of the atoms is controversial, the ex ...
Speech-based degree of sleepiness estimation is an emerging research problem. In the literature, this problem has been mainly addressed through modeling of low level of descriptors. This paper investigates an end-to-end approach, where given raw waveform a ...
This work tests several classification techniques and acoustic features and further combines them using late fusion to classify paralinguistic information for the ComParE 2018 challenge. We use Multiple Linear Regression (MLR) with Ordinary Least Squares ( ...
Conventional deep neural networks (DNN) for speech acoustic modeling rely on Gaussian mixture models (GMM) and hidden Markov model (HMM) to obtain binary class labels as the targets for DNN training. Subword classes in speech recognition systems correspond ...
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