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Speech and Language Processing:An Introduction to Natural Language Processing,Computational Linguistics,and Speech Recognition
Speech and Language Processing Introduction to Natural Language Processing Computational Linguistics Speech Recognition
2015/8/25
Jurafsky and Martin’s long-awaited text sets a new gold standard that will be difficult to surpass, as attested by the flurry of glowing reviews that accompanied its publication early this year.1 In a...
Speech Recognition without a Lexicon - Bridging the Gap between Graphemic and Phonetic Systems
lexicon learning pronunciation modeling
2014/11/27
Modern speech recognizers rely on three core components: an acoustic model, a language model, and a pronunciation lexicon. In order to expand speech recognition capability to lowresource languages and...
Updated MINDS Report on Speech Recognition and Understanding, Part 2
Updated MINDS Report Speech Recognition Understanding
2014/11/27
This article is the second partof an updated version of the“MINDS 2006–2007 Reportof the Speech UnderstandingWorking Group,” one of five reports emanating from two workshops entitled “Meeting of the M...
DISCRIMINATIVE TRAINING OF HIERARCHICAL ACOUSTIC MODELS FOR LARGE VOCABULARY CONTINUOUS SPEECH RECOGNITION
hierarchical acoustic modeling discriminative training LVCSR
2014/11/27
In this paper we propose discriminative training of hierarchical acoustic models for large vocabulary continuous speech recognition tasks. After presenting our hierarchical modeling framework, we desc...
FLEXIBLE MULTI-STREAM FRAMEWORK FOR SPEECH RECOGNITION USING MULTI-TAPE FINITE-STATE TRANSDUCERS
FLEXIBLE MULTI-STREAM FRAMEWORK SPEECH RECOGNITION MULTI-TAPE FINITE-STATE TRANSDUCERS
2014/11/27
We present an approach to general multi-stream recognition utilizing multi-tape finite-state transducers (FSTs). The approach is novel in that each of the multiple “streams” of features can represent ...
PRODUCTION DOMAIN MODELING OF PRONUNCIATION FOR VISUAL SPEECH RECOGNITION
PRODUCTION DOMAIN MODELING PRONUNCIATION VISUAL SPEECH RECOGNITION
2014/11/27
Articulatory feature models have been proposed in the automatic speech recognition community as an alternative to phone-based models ofspeech. In this paper, we extend this approach to the visual moda...
A probabilistic framework for segment-base d speech recognition
probabilistic framework segment-based speech recognition
2014/11/27
Most current speech recognizers use an observation space based on a temporal sequence of measurements extracted from fixed-length ‘‘frames’’ (e.g., Mel-cepstra). Given a hypothetical word or sub-word ...
BAUM-WELCH TRAINING FOR SEGMENT-BASED SPEECH RECOGNITION
BAUM-WELCH TRAINING SEGMENT-BASED SPEECH RECOGNITION.
2014/11/27
BAUM-WELCH TRAINING FOR SEGMENT-BASED SPEECH RECOGNITION.
Hidden Feature Models for Speech Recognition Using Dynamic Bayesian Networks
Hidden Feature Models Speech Recognition Dynamic Bayesian Networks
2014/11/27
In this paper, we investigate the use of dynamic Bayesian networks (DBNs) to explicitly represent models of hidden features,such as articulatory or other phonological features, for automatic speech re...
Multimodal Speech Recognition with Ultrasonic Sensors
multimodal ultrasonic speech recognition
2014/11/27
In this research we explore multimodal speech recognition by augmenting acoustic information with that obtained by an ultrasonic emitter and receiver. After designing a hardware component to generate ...