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Found 7 papers, 2 papers with code
Comparing CTC and LFMMI for out-of-domain adaptation of wav2vec 2.0 acoustic model
On Switchboard (300h) we obtain relative improvements of 33% and 35% respectively.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Lattice-Free MMI Adaptation Of Self-Supervised Pretrained Acoustic Models
In this work, we propose lattice-free MMI (LFMMI) for supervised adaptation of self-supervised pretrained acoustic model.
Pkwrap: a PyTorch Package for LF-MMI Training of Acoustic Models
We present a simple wrapper that is useful to train acoustic models in PyTorch using Kaldi's LF-MMI training framework.
Audio and Speech Processing Sound
Neural Network based End-to-End Query by Example Spoken Term Detection
Here, we show that the CNN based matching outperforms DTW based matching using bottleneck features as well.
Multilingual Bottleneck Features for Query by Example Spoken Term Detection
State of the art solutions to query by example spoken term detection (QbE-STD) usually rely on bottleneck feature representation of the query and audio document to perform dynamic time warping (DTW) based template matching.
Information Theoretic Analysis of DNN-HMM Acoustic Modeling
We propose an information theoretic framework for quantitative assessment of acoustic modeling for hidden Markov model (HMM) based automatic speech recognition (ASR).
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
On Structured Sparsity of Phonological Posteriors for Linguistic Parsing
Building on findings from converging linguistic evidence on the gestural model of Articulatory Phonology as well as the neural basis of speech perception, we hypothesize that phonological posteriors convey properties of linguistic classes at multiple time scales, and this information is embedded in their support (index) of active coefficients.
