Modelling the effects of spontaneous speech in speech recognition
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hdl:2117/20204
Tipus de documentText en actes de congrés
Data publicació2013
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Abstract
Intrinsic variability of the speaker in spontaneous speech
remains a challenge to state of the art Automatic speech
recognition (ASR). While planned speech exhibits a
moderate variability, the significant variability of spontaneous
speech is caused by situation, context, intention,
emotion and listeners. This conditioning of speech is observable
in terms of speaking rate and in feature space.
We analysed broadcast news (BN) and broadcast conversational
(BC) speech in terms of phoneme rate (PR) and
feature space reduction (FSR), and contrasted both with
the planned speech data. Strong statistically significant
differences were revealed. We cluster the speech segments
with respect to their degree of PR and FSR forming
a set of variability classes, and induce the variability
classes into the Hidden-Markov-Model (HMM) based
acoustic model (AM).
In recognition we follow two approaches: the first
considers the variability class as context variable, the second
relies on prior estimation of the variability class after
the first pass of a multi-pass recognition system. Beside
explicit modelling of the intrinsic speech variability
of the speaker, we furthermore segregate the general
speaker specific characteristics by means of speaker
adaptive training (SAT) into feature space transforms using
ConstrainedMaximumLikelihood Linear Regression
(CMLLR), and apply the adaptive approach in third pass
recognition.
By approaching to model both within speaker variation
and between speaker variation in spontaneous
speech, we address two fundamental sources of speech variability that determine the performance of ASR systems.
CitacióShulz, H.; Fonollosa, José A. R. Modelling the effects of spontaneous speech in speech recognition. A: Speech Processing Conference. "2013 Speech Processing Conference: conference proceedings: July 1-2, 2013: AFEKA, Tel-Aviv Academic College of Engineering". Tel-Aviv: 2013.
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