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Found 6 papers, 2 papers with code
End-to-End Training of a Neural HMM with Label and Transition Probabilities
We investigate recognition results and additionally Viterbi alignments of our models.
Development of Hybrid ASR Systems for Low Resource Medical Domain Conversational Telephone Speech
Language barriers present a great challenge in our increasingly connected and global world.
Improved Robustness to Disfluencies in RNN-Transducer Based Speech Recognition
Automatic Speech Recognition (ASR) based on Recurrent Neural Network Transducers (RNN-T) is gaining interest in the speech community.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+1
Context-Dependent Acoustic Modeling without Explicit Phone Clustering
In this work, we address a direct phonetic context modeling for the hybrid deep neural network (DNN)/HMM, that does not build on any phone clustering algorithm for the determination of the HMM state inventory.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
+2
Sample Drop Detection for Distant-speech Recognition with Asynchronous Devices Distributed in Space
The candidate time windows are selected from a set of large time intervals, possibly including a sample drop, and by using a preprocessing step.
Sound Audio and Speech Processing I.2.7
Extended pipeline for content-based feature engineering in music genre recognition
We present a feature engineering pipeline for the construction of musical signal characteristics, to be used for the design of a supervised model for musical genre identification.
