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498 results on '"O’Shaughnessy, Douglas"'

166. Robust speech recognition under noisy environments using asymmetric tapers.

Author

Alam, Md Jahangir, Kenny, Patrick, and O'Shaughnessy, Douglas

Abstract

This paper presents asymmetric taper (or window)-based robust Mel frequency cepstral coefficient (MFCC) feature extraction for automatic speech recognition (ASR). Commonly, MFCC features are computed from a symmetric Hamming-tapered direct-spectrum estimate. Symmetric tapers have linear phase and also imply longer time delay. In ASR systems, phase information is usually discarded as human speech perception is relatively insensitive to short-time phase distortion. So, any linearity constraint on phase can be removed without adverse effects. Use of asymmetric tapers, having better frequency response and shorter time delay, for MFCC feature extraction in speech recognition can lead to better recognition performance. Using our proposed method it is possible to introduce asymmetry in any symmetric taper by adjusting only one additional parameter, which controls the degree of asymmetry. Experimental results on the AURORA-2 corpus show that the proposed asymmetric tapers outperform the symmetric Hamming taper in terms of word accuracy both in clean and noisy environments. [ABSTRACT FROM PUBLISHER]

Published
2012

167. LDA-based LM adaptation using latent semantic marginals and minimum discriminant information.

Author

Haidar, Md. Akmal and O'Shaughnessy, Douglas

Abstract

We introduce an unsupervised language model (LM) adaptation approach using latent Dirichlet allocation (LDA) and latent semantic marginals (LSM). LSM is a unigram probability distribution over words and is estimated using the LDA model. A hard-clustering method is used to form topics. Each document is assigned to a topic based on the maximum number of words chosen from the topic for that document in LDA analysis. An LDA-adapted model is created using the weighted combination of topic models. The LDA-adapted model is modified by using the LSM as dynamic marginals, and a new adapted model is formed by using the minimum discriminant information (MDI) approach, which minimizes the distance between the new adapted model and the LDA-adapted model. We apply LM adaptation approaches for original and automatic (recognition results after first-pass decoding) transcriptions test data and have seen significant perplexity and word error rate (WER) reductions over a traditional approach. [ABSTRACT FROM PUBLISHER]

Published
2012

175. Formant Estimation and Tracking.

Author

O′Shaughnessy, Douglas

Abstract

This chapter deals with the estimation formant estimation and tracking of the movements of the spectral resonances of human formant vocal tracts, also known as formants. The representation or modeling of speech in terms of formants is useful in several areas of speech processing: coding, recognition, synthesis, and enhancement, as formants efficiently describe essential aspects of speech using a very limited set of parameters. However, estimating formants is more difficult than simply searching for peaks in an amplitude spectrum, as the spectral peaks of vocal-tract output depend upon a variety for factors in complicated ways: vocal-tract shape, excitation, and periodicity. We describe in detail the formal task of formant tracking, and explore its successes and difficulties, as well as giving reasons for the various approaches. [ABSTRACT FROM AUTHOR]

Published
2008
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178. A Hybrid Genetic-Neural Front-End Extension for Robust Speech Recognition over Telephone Lines.

Author

Carbonell, Jaime G., Siekmann, Jörg, Chetouani, Mohamed, Hussain, Amir, Gas, Bruno, Milgram, Maurice, Zarader, Jean-Luc, Selouani, Sid-Ahmed, Hamam, Habib, and O'Shaughnessy, Douglas

Abstract

This paper presents a hybrid technique combining the Karhonen-Loeve Transform (KLT), the Multilayer Perceptron (MLP) and Genetic Algorithms (GAs) to obtain less-variant Mel-frequency parameters. The advantages of such an approach are that the robustness can be reached without modifying the recognition system, and that neither assumption nor estimation of the noise are required. To evaluate the effectiveness of the proposed approach, an extensive set of continuous speech recognition experiments are carried out by using the NTIMIT telephone speech database. The results show that the proposed approach outperforms the baseline and conventional systems. [ABSTRACT FROM AUTHOR]

Published
2007
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183. SPEECH PROCESSING.

Author

O'Shaughnessy, Douglas

Subjects
SPEECH processing systems, SPEECH perception, DIGITAL signal processing, SPEECH, SPEECH synthesis, DIGITAL communications
Abstract

The article examines ways that computers use to analyze speech and to simulate production or perception of speech signals. There are many applications for speech processing: text-to-speech synthesis, speech recognition, speaker verification, and speech coding. All these uses require converting the original speech into a compact digital form, or vice versa, and related digital signal processing. The objective of speech analysis is to transform speech samples into a more useful information representation, for specific objectives other than simply furnishing speech to human ears.

Published
2003

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