KL Realignment for Speaker Diarization with Multiple Feature Streams
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In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...
In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...
What does a blind entity need in order to determine the geometry of the set of photocells that it carries through a changing lightfield? In this paper, we show that very crude knowledge of some statistical properties of the environment is sufficient for th ...
This paper investigates the use of phoneme class conditional probabilities as features (posterior features) for template-based ASR. Using 75 words and 600 words task-independent and speaker-independent setup on Phonebook database, we investigate the use of ...
What does a blind entity need in order to determine the geometry of the set of photocells that it carries through a changing lightfield? In this paper, we show that very crude knowledge of some statistical properties of the environment is sufficient for th ...
This work describes a novel system for speaker diarization of meetings recordings based on the combination of acoustic features (MFCC) and Time Delay of Arrivals (TDOA). The first part of the paper analyzes differences between MFCC and TDOA features which ...
In this thesis, we focus on Impulse Radio (IR) Ultra-WideBand (UWB) ranging and positioning techniques under indoor propagation environments. IR-UWB, a new carrierless communication scheme using impulses, is a candidate technology for future communication, ...
This paper aims at investigating the use of Kullback-Leibler (KL) divergence based realignment with application to speaker diarization. The use of KL divergence based realignment operates directly on the speaker posterior distribution estimates and is comp ...
In this thesis, we investigate the use of posterior probabilities of sub-word units directly as input features for automatic speech recognition (ASR). These posteriors, estimated from data-driven methods, display some favourable properties such as increase ...
Milestones in sparse signal reconstruction and compressive sensing can be understood in a probabilistic Bayesian context, fusing underdetermined measurements with knowledge about low level signal properties in the posterior distribution, which is maximized ...
Institute of Electrical and Electronics Engineers2010
