Huang, 2019
ViewHTML| Publication | Publication Date | Title |
|---|---|---|
| CN112712804B (en) | Speech recognition method, system, medium, computer device, terminal and application | |
| Huang et al. | Recurrent poisson process unit for speech recognition | |
| US10325200B2 (en) | Discriminative pretraining of deep neural networks | |
| Graves et al. | Bidirectional LSTM networks for improved phoneme classification and recognition | |
| Deng et al. | Deep learning for signal and information processing | |
| Passricha et al. | Convolutional neural networks for raw speech recognition | |
| Deng et al. | Foundations and trends in signal processing: Deep learning–methods and applications | |
| Cui et al. | Multi-view and multi-objective semi-supervised learning for hmm-based automatic speech recognition | |
| Dekel et al. | An online algorithm for hierarchical phoneme classification | |
| Dua et al. | Discriminatively trained continuous Hindi speech recognition system using interpolated recurrent neural network language modeling | |
| Huang et al. | Deep graph random process for relational-thinking-based speech recognition | |
| US20240153508A1 (en) | End-to-End Speech Recognition Adapted for Multi-Speaker Applications | |
| Hazmoune et al. | A new hybrid framework based on hidden Markov models and K-nearest neighbors for speech recognition | |
| CN115376547B (en) | Pronunciation evaluation method, pronunciation evaluation device, computer equipment and storage medium | |
| Wöllmer et al. | Noise robust ASR in reverberated multisource environments applying convolutive NMF and Long Short-Term Memory | |
| Zhao et al. | Ensemble learning approaches in speech recognition | |
| Saraçlar | Pronunciation modeling for conversational speech recognition | |
| Becerra et al. | A comparative case study of neural network training by using frame-level cost functions for automatic speech recognition purposes in Spanish | |
| Huang | Recurrent poisson process unit for automatic speech recognition | |
| Abdel-Haleem | Conditional random fields for continuous speech recognition | |
| Najkar et al. | An evolutionary decoding method for HMM-based continuous speech recognition systems using particle swarm optimization | |
| Räsänen et al. | A noise robust method for pattern discovery in quantized time series: the concept matrix approach. | |
| Shinozaki et al. | Automated development of dnn based spoken language systems using evolutionary algorithms | |
| Kannan | Adaptation of spectral trajectory models for large vocabulary continuous speech recognition | |
| Li | Cycle-consistent adversarial networks for automatic speech recognition |