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Variable-length acoustic units inference for text-to-speech synthesis
2001
7th European Conference on Speech Communication and Technology (Eurospeech 2001)
unpublished
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This technique is widely used to infer hidden Markov random processes. ...
Indeed, let us postulate a large enough number of observed sequences and an ergodic source process. The entropy calculated through the model is denoted À ½ Ç ÐÓ ¾ È ´Çµ. ...
doi:10.21437/eurospeech.2001-261
fatcat:jsb4buacobghngak2pzopokaxe
Language modeling by variable length sequences: theoretical formulation and evaluation of multigrams
1995 International Conference on Acoustics, Speech, and Signal Processing
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We show that estimates of the model parameters can be computed through an iterative Expectation-Maximization algorithm and we describe a forward-backward procedure for its implementation. ...
We report the results of a systematical evaluation of multigrams for language modeling on the ATIS database. The objective performance measure is the test set perplexity. ...
To a certain extent, a n-multigram model can be thought of as a n-state Ergodic Hidden Markov Model (EHMM) with state i emitting a sequence of length i, and all transition probabilities being equal. ...
doi:10.1109/icassp.1995.479391
dblp:conf/icassp/DeligneB95
fatcat:opbdpt4etngstga4qnfr42ccqq
How Do Neural Sequence Models Generalize? Local and Global Cues for Out-of-Distribution Prediction
2021
Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
unpublished
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A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
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Ergodic hidden
Markov models and polygrams for language mod- Alec Radford, Jeffrey Wu, Rewon Child, David Luan,
eling. In Proceedings of ICASSP’94. ...
can be reli- schemes in controlling out-of-distribution be-
ably estimated (e.g. just the final word; Katz 1987), havior.
and hidden Markov models explicitly integrate ...
doi:10.18653/v1/2021.emnlp-main.448
fatcat:5ecowb2cvrfvfij2ijvw72wev4