Boosting Localized Features for Speaker and Speech Recognition
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Modern speech recognition has many ways of quantifying the misrecognitions a speech recognizer makes. The errors in modern speech recognition makes extensive use of the Levenshtein algorithm to find the distance between the labeled target and the recognize ...
Humans perceive their surrounding environment in a multimodal manner by using multi-sensory inputs combined in a coordinated way. Various studies in psychology and cognitive science indicate the multimodal nature of human speech production and perception. ...
This paper describes an approach where posterior-based features are applied in those recognition tasks where the amount of training data is insufficient to obtain a reliable estimate of the speech variability. A template matching approach is considered in ...
The AMI and AMIDA projects are concerned with the recognition and interpretation of multiparty meetings. Within these projects we have: developed an infrastructure for recording meetings using multiple microphones and cameras; released a 100 hour annotated ...
In this paper we present a study of automatic speech recognition systems using context-dependent phonemes and graphemes as sub-word units based on the conventional HMM/GMM system as well as tandem system. Experimental studies conducted on three different c ...
In this paper, we present a novel feature normalization method in the log-scaled spectral domain for improving the noise robustness of speech recognition front-ends. In the proposed scheme, a non-linear contrast stretching is added to the outputs of log me ...
This paper presents our approach for automatic speech recognition (ASR) of overlapping speech. Our system consists of two principal components: a speech separation component and a feature estmation component. In the speech separation phase, we first estima ...
This paper investigates a multilayer perceptron (MLP) based acoustic feature mapping to extract robust features for automatic speech recognition (ASR) of overlapping speech. The MLP is trained to learn the mapping from log mel filter bank energies (MFBEs) ...
The AMI and AMIDA projects are concerned with the recognition and interpretation of multiparty meetings. Within these projects we have: developed an infrastructure for recording meetings using multiple microphones and cameras; released a 100 hour annotated ...
Speaker detection is an important component of a speech-based user interface. Audiovisual speaker detection, speech and speaker recognition or speech synthesis for example find multiple applications in human-computer interaction, multimedia content indexin ...
