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Performance of a typical automatic speech recognition (ASR) system severely degrades when it encounters speech from reverberant environments. Part of the reason for this degradation is the feature extraction techniques that use analysis windows which are m ...
This paper proposes a Distant Speech Recognition system based on a novel speaker Localization and Beamforming (SRLB) algorithm. To localize the speaker an algorithm based on Steered Response Power by utilizing harmonic structures of speech signal is propos ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models~(HMMs), with a p ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models (HMMs), with a p ...
The goal of this thesis is to develop and design new feature representations that can improve the automatic speech recognition (ASR) performance in clean as well noisy conditions. One of the main shortcomings of the fixed scale (typically 20-30 ms long ana ...
Performance of a typical automatic speech recognition (ASR) system severely degrades when it encounters speech from reverberant environments. Part of the reason for this degradation is the feature extraction techniques that use analysis windows which are m ...
Real world applications such as hands-free dialling in cars may have to perform recognition of spoken digits in potentially very noisy environments. Existing state-of-the-art solutions to this problem use feature-based Hidden Markov Models (HMMs), with a p ...
This paper proposes a simple, computationally efficient 2-mixture model approach to discrimination between speech and background noise. It is directly derived from observations on real data, and can be used in a fully unsupervised manner, with the EM algor ...
The recognition of speech in meetings poses a number of challenges to current Automatic Speech Recognition (ASR) techniques. Meetings typically take place in rooms with non-ideal acoustic conditions and significant background noise, and may contain large s ...
Detection and localization of speakers with microphone arrays is a difficult task due to the wideband nature of speech signals, the large amount of overlaps between speakers in spontaneous conversations, and the presence of noise sources. Many existing aud ...
