Search Results for author:
Found 5 papers, 1 papers with code
LT-LM: a novel non-autoregressive language model for single-shot lattice rescoring
We propose a novel rescoring approach, which processes the entire lattice in a single call to the model.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Target-Speaker Voice Activity Detection: a Novel Approach for Multi-Speaker Diarization in a Dinner Party Scenario
We propose a novel Target-Speaker Voice Activity Detection (TS-VAD) approach, which directly predicts an activity of each speaker on each time frame.
Exploring Gaussian mixture model framework for speaker adaptation of deep neural network acoustic models
Experimental results on the TED-LIUM corpus show that the proposed adaptation technique can be effectively integrated into DNN and TDNN setups at different levels and provide additional gain in recognition performance: up to 6% of relative word error rate reduction (WERR) over the strong feature-space adaptation techniques based on maximum likelihood linear regression (fMLLR) speaker adapted DNN baseline, and up to 18% of relative WERR in comparison with a speaker independent (SI) DNN baseline model, trained on conventional features.
Fast and Accurate OOV Decoder on High-Level Features
The proposed approach is based on using high-level features from an automatic speech recognition (ASR) system, so called phoneme posterior based (PPB) features, for decoding.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Exploration de param\`etres acoustiques d\'eriv\'es de GMM pour l'adaptation non supervis\'ee de mod\`eles acoustiques \`a base de r\'eseaux de neurones profonds (Exploring GMM-derived features for unsupervised adaptation of deep neural network acoustic models)
L{'}{\'e}tude pr{\'e}sent{\'e}e dans cet article am{\'e}liore une m{\'e}thode r{\'e}cemment propos{\'e}e pour l{'}adaptation de mod{\`e}les acoustiques markoviens coupl{\'e}s {\`a} un r{\'e}seau de neurones profond (DNN-HMM).
